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Viral04/CUAD_Finetuned

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  1. README.md +12 -7
  2. adapter_model.safetensors +1 -1
  3. runs/Mar19_16-12-38_637e4b325ea6/events.out.tfevents.1710864847.637e4b325ea6.3354.0 +3 -0
  4. runs/Mar19_16-15-58_637e4b325ea6/events.out.tfevents.1710865008.637e4b325ea6.3354.1 +3 -0
  5. runs/Mar19_16-17-47_637e4b325ea6/events.out.tfevents.1710865070.637e4b325ea6.3354.2 +3 -0
  6. runs/Mar19_16-56-50_637e4b325ea6/events.out.tfevents.1710867412.637e4b325ea6.16722.0 +3 -0
  7. training_args.bin +1 -1
README.md CHANGED
@@ -20,7 +20,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on the generator dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3202
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  ## Model description
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@@ -46,18 +46,23 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: constant
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  - lr_scheduler_warmup_steps: 0.03
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- - training_steps: 100
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 1.4597 | 0.0 | 20 | 1.3668 |
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- | 1.4026 | 0.0 | 40 | 1.3473 |
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- | 1.4525 | 0.01 | 60 | 1.3343 |
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- | 1.4547 | 0.01 | 80 | 1.3256 |
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- | 1.3827 | 0.01 | 100 | 1.3202 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on the generator dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.3268
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: constant
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  - lr_scheduler_warmup_steps: 0.03
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+ - training_steps: 200
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.4515 | 0.0 | 20 | 1.3677 |
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+ | 1.4001 | 0.0 | 40 | 1.3462 |
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+ | 1.4109 | 0.01 | 60 | 1.3316 |
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+ | 1.3631 | 0.01 | 80 | 1.3256 |
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+ | 1.3463 | 0.01 | 100 | 1.3231 |
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+ | 1.3541 | 0.01 | 120 | 1.3173 |
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+ | 1.3072 | 0.01 | 140 | 1.3156 |
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+ | 1.2798 | 0.02 | 160 | 1.3114 |
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+ | 1.3276 | 0.02 | 180 | 1.3143 |
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+ | 1.2681 | 0.02 | 200 | 1.3268 |
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  ### Framework versions
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