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  1. README.md +26 -18
  2. adapter_config.json +2 -0
  3. adapter_model.safetensors +3 -0
README.md CHANGED
@@ -1,10 +1,11 @@
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  ---
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  license: apache-2.0
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- base_model: distilbert-base-uncased
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  tags:
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  - generated_from_trainer
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  metrics:
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  - accuracy
 
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  model-index:
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  - name: distilbert-base-uncased-lora-text-classification
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  results: []
@@ -15,10 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # distilbert-base-uncased-lora-text-classification
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- This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0684
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- - Accuracy: {'accuracy': 0.879}
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  ## Model description
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@@ -49,21 +50,28 @@ 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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- | No log | 1.0 | 250 | 0.4266 | {'accuracy': 0.87} |
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- | 0.4232 | 2.0 | 500 | 0.4260 | {'accuracy': 0.88} |
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- | 0.4232 | 3.0 | 750 | 0.5071 | {'accuracy': 0.885} |
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- | 0.2213 | 4.0 | 1000 | 0.7424 | {'accuracy': 0.875} |
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- | 0.2213 | 5.0 | 1250 | 0.7885 | {'accuracy': 0.881} |
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- | 0.067 | 6.0 | 1500 | 0.9312 | {'accuracy': 0.872} |
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- | 0.067 | 7.0 | 1750 | 0.9669 | {'accuracy': 0.874} |
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- | 0.0238 | 8.0 | 2000 | 1.0856 | {'accuracy': 0.874} |
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- | 0.0238 | 9.0 | 2250 | 1.0637 | {'accuracy': 0.88} |
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- | 0.0066 | 10.0 | 2500 | 1.0684 | {'accuracy': 0.879} |
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.32.1
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- - Pytorch 2.0.1
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- - Datasets 2.14.4
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- - Tokenizers 0.13.2
 
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  ---
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  license: apache-2.0
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+ library_name: peft
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  tags:
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  - generated_from_trainer
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  metrics:
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  - accuracy
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+ base_model: distilbert-base-uncased
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  model-index:
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  - name: distilbert-base-uncased-lora-text-classification
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  results: []
 
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  # distilbert-base-uncased-lora-text-classification
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9162
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+ - Accuracy: {'accuracy': 0.901}
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:-------------------:|
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+ | No log | 1.0 | 250 | 0.3611 | {'accuracy': 0.871} |
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+ | 0.4182 | 2.0 | 500 | 0.5356 | {'accuracy': 0.883} |
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+ | 0.4182 | 3.0 | 750 | 0.5292 | {'accuracy': 0.899} |
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+ | 0.2132 | 4.0 | 1000 | 0.5966 | {'accuracy': 0.897} |
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+ | 0.2132 | 5.0 | 1250 | 0.6869 | {'accuracy': 0.894} |
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+ | 0.0748 | 6.0 | 1500 | 0.7645 | {'accuracy': 0.898} |
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+ | 0.0748 | 7.0 | 1750 | 0.8095 | {'accuracy': 0.897} |
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+ | 0.0335 | 8.0 | 2000 | 0.9055 | {'accuracy': 0.892} |
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+ | 0.0335 | 9.0 | 2250 | 0.9086 | {'accuracy': 0.901} |
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+ | 0.0083 | 10.0 | 2500 | 0.9162 | {'accuracy': 0.901} |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.1+cu121
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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+ ## Training procedure
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  ### Framework versions
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+
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+ - PEFT 0.6.2
 
 
adapter_config.json CHANGED
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  {
 
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  "auto_mapping": null,
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  "base_model_name_or_path": "distilbert-base-uncased",
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  "bias": "none",
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  "modules_to_save": null,
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  "peft_type": "LORA",
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  "r": 4,
 
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  "revision": null,
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  "target_modules": [
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  "q_lin"
 
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  {
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+ "alpha_pattern": {},
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  "auto_mapping": null,
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  "base_model_name_or_path": "distilbert-base-uncased",
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  "bias": "none",
 
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  "modules_to_save": null,
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  "peft_type": "LORA",
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  "r": 4,
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+ "rank_pattern": {},
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  "revision": null,
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  "target_modules": [
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  "q_lin"
adapter_model.safetensors ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:d7115f52b941aa039350b290b079fc1d32a3bb16fbbe8bc1058922327876e50a
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+ size 2518104