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End of training

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Files changed (6) hide show
  1. README.md +12 -12
  2. config.json +3 -4
  3. model.safetensors +2 -2
  4. tokenizer.json +1 -6
  5. tokenizer_config.json +3 -1
  6. training_args.bin +1 -1
README.md CHANGED
@@ -1,6 +1,6 @@
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  ---
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  license: mit
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- base_model: thenlper/gte-base
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -15,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # Classify-model-v1.2
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- This model is a fine-tuned version of [thenlper/gte-base](https://huggingface.co/thenlper/gte-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4658
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- - Accuracy: 0.8571
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  ## Model description
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@@ -37,7 +37,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0001
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  - train_batch_size: 128
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  - eval_batch_size: 128
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  - seed: 42
@@ -49,13 +49,13 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.5854 | 1.0 | 11 | 1.2455 | 0.5982 |
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- | 1.0011 | 2.0 | 22 | 0.7630 | 0.7679 |
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- | 0.5023 | 3.0 | 33 | 0.5095 | 0.8393 |
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- | 0.2185 | 4.0 | 44 | 0.4658 | 0.8304 |
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- | 0.0995 | 5.0 | 55 | 0.4605 | 0.8571 |
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- | 0.0582 | 6.0 | 66 | 0.4858 | 0.8482 |
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- | 0.0392 | 7.0 | 77 | 0.4658 | 0.8571 |
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  ### Framework versions
 
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  ---
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  license: mit
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+ base_model: thenlper/gte-small
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # Classify-model-v1.2
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+ This model is a fine-tuned version of [thenlper/gte-small](https://huggingface.co/thenlper/gte-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5391
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+ - Accuracy: 0.8661
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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  - train_batch_size: 128
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  - eval_batch_size: 128
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.6187 | 1.0 | 11 | 1.2743 | 0.6875 |
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+ | 1.0031 | 2.0 | 22 | 0.8051 | 0.8482 |
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+ | 0.5518 | 3.0 | 33 | 0.5952 | 0.8661 |
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+ | 0.3103 | 4.0 | 44 | 0.5251 | 0.8571 |
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+ | 0.2119 | 5.0 | 55 | 0.5139 | 0.8661 |
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+ | 0.162 | 6.0 | 66 | 0.5225 | 0.8661 |
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+ | 0.1419 | 7.0 | 77 | 0.5391 | 0.8661 |
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  ### Framework versions
config.json CHANGED
@@ -1,14 +1,13 @@
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  {
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- "_name_or_path": "thenlper/gte-base",
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  "architectures": [
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  "BertForSequenceClassification"
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  ],
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  "attention_probs_dropout_prob": 0.1,
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  "classifier_dropout": null,
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  "hidden_act": "gelu",
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  "hidden_dropout_prob": 0.1,
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- "hidden_size": 768,
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  "id2label": {
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  "0": "LABEL_0",
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  "1": "LABEL_1",
@@ -18,7 +17,7 @@
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  "5": "LABEL_5"
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- "intermediate_size": 3072,
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  "label2id": {
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+ "_name_or_path": "thenlper/gte-small",
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  "classifier_dropout": null,
 
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  "hidden_act": "gelu",
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  "id2label": {
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  "0": "LABEL_0",
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  "1": "LABEL_1",
 
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  "5": "LABEL_5"
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tokenizer_config.json CHANGED
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