Add new SentenceTransformer model
Browse files- README.md +75 -76
- model.safetensors +1 -1
README.md
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- loss:TripletLoss
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base_model: distilbert/distilroberta-base
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widget:
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hope that one day there will be no need for you to observe any restrictions.
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sentences:
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sentences:
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sentences:
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- '
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Spock, Scotty, come with me. Report, Spock. The multitronic unit is drawing more
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and more power directly from the warp engines. The computer now controls all helm,
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navigation, and engineering functions. And communications and fire control.[SEP]We'll
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reach the rendezvous point for the war games within an hour. We must regain control
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of the ship by then.
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sentences:
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you're describing Is non-existence. Standard General Alert signal from Starfleet
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Command, Captain.[SEP]All stations to immediate alert status. Stand by.
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sentences:
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- Captain, scanners now report a life object on the planet surface below.
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pipeline_tag: sentence-similarity
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library_name: sentence-transformers
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metrics:
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type: evaluator_enc
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metrics:
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- type: cosine_accuracy
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value: 0.
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name: Cosine Accuracy
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- task:
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type: triplet
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type: evaluator_val
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metrics:
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- type: cosine_accuracy
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value: 0.
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name: Cosine Accuracy
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---
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model = SentenceTransformer("greatakela/gnlp_hw1_encoder")
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# Run inference
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sentences = [
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'
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]
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embeddings = model.encode(sentences)
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print(embeddings.shape)
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| Metric | evaluator_enc | evaluator_val |
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|:--------------------|:--------------|:--------------|
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| **cosine_accuracy** | **0.
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<!--
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## Bias, Risks and Limitations
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* Size: 4,893 training samples
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* Columns: <code>sentence_0</code>, <code>sentence_1</code>, and <code>sentence_2</code>
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* Approximate statistics based on the first 1000 samples:
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| | sentence_0 | sentence_1
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| type | string | string
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| details | <ul><li>min: 2 tokens</li><li>mean: 83.
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* Samples:
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| sentence_0
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| <code>
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* Loss: [<code>TripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#tripletloss) with these parameters:
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```json
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{
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### Training Logs
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| Epoch | Step | Training Loss | evaluator_enc_cosine_accuracy | evaluator_val_cosine_accuracy |
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|:------:|:----:|:-------------:|:-----------------------------:|:-----------------------------:|
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| -1 | -1 | - | 0.
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| 0.4902 | 300 | - | 0.
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| 0.8170 | 500 | 1.
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| 0.9804 | 600 | - | 0.
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| 1.0 | 612 | - | 0.
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| 1.4706 | 900 | - | 0.
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| 1.6340 | 1000 | 0.
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| 1.9608 | 1200 | - | 0.
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| 2.0 | 1224 | - | 0.
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| 2.4510 | 1500 | 0.
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| 2.9412 | 1800 | - | 0.
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| 3.0 | 1836 | - | 0.
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| -1 | -1 | - | - | 0.
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### Framework Versions
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- loss:TripletLoss
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base_model: distilbert/distilroberta-base
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widget:
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- source_sentence: Leave me alone! Have you gone daft? Mister Spock needs me! Let
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go! That will be quite enough. Thank you, doctor.; Please, release her.[SEP]What's
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this all about?
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sentences:
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- ' You know, the lab here, they have a paid intern position. It''s usually given
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to one of the kids from the universities but, if you want, I could pRobably get
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you an interview. There''s some entry lEvel stuff, some gofer work. But you''d
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also have access to a lot of cool things.'
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- She was doing as I requested, Mister Scott. A Vulcan form of self-healing.
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- Thasians have been referred to in our records as having the power to transmute
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objects or render substances invisible. It has generally been regarded as legend,
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but Charlie does seems to possess this same power.
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- source_sentence: Why would you do this? Because the needs of the one ...outweigh
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the needs of the many. I have been ...and ever shall be ...your friend. Yes! Yes,
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Spock. The ship. ...Out of danger?[SEP]You saved the ship, ...You saved us all.
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Don't you remember?
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sentences:
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- ' My wife had taken a sleeping pill and gone to bed. It was Christmas Eve. Kyle
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popped corn in the fireplace. He Managed to knock loose some tinder. Wrapping
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paper caught on fire. Spread so fast. I got Kyle outta there. When I went back
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in for... [Chokes, takes a beat, then.]'
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- In two days, you'll have your own hands, Thalassa. Mechanically efficient and
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quite human-looking. Android robot hands, of course. Hands without feeling. Enjoy
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the taste of life while you can.
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- Jim, ...your name is Jim.
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- source_sentence: Captain, if something hasn't worked out and therefore has no scientific
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fact Shall we leave it up to the doctor? Since you brought me down here for advice,
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Captain One of the advantages of being a Captain, Doctor, is being able to ask
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for advice without necessarily having to take it. I think I'll have to award that
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round to the Captain, Helen. You're fighting over your weight. All right, let's
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take a look.[SEP]I'm not a criminal! I do not require neural neutraliser.
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sentences:
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- Neural neutraliser. Can you explain that, Doctor Van Gelder?
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- ' And the disorientation?'
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- I'm aware of these facts. Please get on with the job. Computer.
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- source_sentence: We're picking up an object, sir. Much larger, coming toward us.
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Coming. Exceptionally strong contact. Not visual yet. Distant spectrograph. Metallic,
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similar to cube. Much greater energy reading. There, sir. Half speed. Prepare
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for evasive action.[SEP]Reducing to warp two, sir.
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sentences:
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- Tractor beam, Captain. Something's grabbed us, hard.
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- Exactly.
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- ' There''s a blockage in the urinary tract. Simple terms, your baby can''t pee.
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His bladder is swollen and it''s crushing his lungs.'
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- source_sentence: My father says you have been my friend. ...You came back for me.
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You would have done the same for me. Why would you do this? Because the needs
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of the one ...outweigh the needs of the many. I have been ...and ever shall be
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...your friend.[SEP]Yes! Yes, Spock.
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sentences:
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- But a defensible entrance, Captain.
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- ' No, blood tests were all normal. And he clotted in six minutes.'
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- The ship. ...Out of danger?
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pipeline_tag: sentence-similarity
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library_name: sentence-transformers
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metrics:
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type: evaluator_enc
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metrics:
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- type: cosine_accuracy
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value: 0.9989781379699707
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name: Cosine Accuracy
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- task:
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type: triplet
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type: evaluator_val
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metrics:
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- type: cosine_accuracy
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value: 0.9872685074806213
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name: Cosine Accuracy
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---
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model = SentenceTransformer("greatakela/gnlp_hw1_encoder")
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# Run inference
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sentences = [
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'My father says you have been my friend. ...You came back for me. You would have done the same for me. Why would you do this? Because the needs of the one ...outweigh the needs of the many. I have been ...and ever shall be ...your friend.[SEP]Yes! Yes, Spock.',
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'The ship. ...Out of danger?',
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' No, blood tests were all normal. And he clotted in six minutes.',
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]
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embeddings = model.encode(sentences)
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print(embeddings.shape)
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| Metric | evaluator_enc | evaluator_val |
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|:--------------------|:--------------|:--------------|
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| **cosine_accuracy** | **0.999** | **0.9873** |
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<!--
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## Bias, Risks and Limitations
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* Size: 4,893 training samples
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* Columns: <code>sentence_0</code>, <code>sentence_1</code>, and <code>sentence_2</code>
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* Approximate statistics based on the first 1000 samples:
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| | sentence_0 | sentence_1 | sentence_2 |
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|:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
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| type | string | string | string |
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| details | <ul><li>min: 2 tokens</li><li>mean: 83.38 tokens</li><li>max: 128 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 18.38 tokens</li><li>max: 91 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 18.48 tokens</li><li>max: 102 tokens</li></ul> |
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* Samples:
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| sentence_0 | sentence_1 | sentence_2 |
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|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| <code>The usage is correct. The creator was simply testing your memory banks. There was much damage in the accident. Mister Singh. Come here a moment. This unit will see to your needs. Sir? I'll be back in a moment. Gentlemen, come with me.[SEP]You're on to something, Spock. What is it?</code> | <code>I've correlated all the available information on the Nomad probe, and I'm convinced that this object is indeed that probe.</code> | <code> DIC would explain both the!</code> |
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| <code>Mister Spock, how many people are on Memory Alpha? It varies with the number of scholars, researchers, and scientists from the various Federation planets who are using the computer complex. Captain, we are within orbit range. Lock into orbit. Aye, sir.[SEP]It is leaving Memory Alpha, Captain.</code> | <code>Sensors give no readings of generated energy from Memory Alpha, Captain.</code> | <code> Weird huh?</code> |
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| <code>We're guiding around most of the time ripples now. Mister Spock? All plotted but one, Captain. Coming up on it now. Seems to be fairly heavy displacement. Bones! Get back to your positions. The hypo, Captain.[SEP]It was set for cordrazine.</code> | <code>Empty.</code> | <code> Actually he's only in the Navy when they sang, In The Navy. The rest of the time he's just in generic fatigues. [House stares at him.] What? You brought it up! [House starts to walk out.] You didn't flush.</code> |
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* Loss: [<code>TripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#tripletloss) with these parameters:
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```json
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{
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### Training Logs
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| Epoch | Step | Training Loss | evaluator_enc_cosine_accuracy | evaluator_val_cosine_accuracy |
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|:------:|:----:|:-------------:|:-----------------------------:|:-----------------------------:|
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| -1 | -1 | - | 0.5866 | - |
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| 0.4902 | 300 | - | 0.9875 | - |
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| 0.8170 | 500 | 1.085 | - | - |
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| 0.9804 | 600 | - | 0.9935 | - |
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| 1.0 | 612 | - | 0.9937 | - |
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| 1.4706 | 900 | - | 0.9967 | - |
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| 1.6340 | 1000 | 0.1573 | - | - |
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| 1.9608 | 1200 | - | 0.9980 | - |
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| 2.0 | 1224 | - | 0.9980 | - |
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| 2.4510 | 1500 | 0.0733 | 0.9990 | - |
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| 2.9412 | 1800 | - | 0.9990 | - |
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| 3.0 | 1836 | - | 0.9990 | - |
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| -1 | -1 | - | - | 0.9873 |
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### Framework Versions
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 328485128
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version https://git-lfs.github.com/spec/v1
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oid sha256:2cfe9d7893779dae3c9a4037e4fa4707d7024e9f932525e38aca6809f3070856
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size 328485128
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