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mistral7binstruct_summarize

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<deboramachadoandrade>/mistral-7binstruct-summary-100s

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  1. README.md +10 -10
  2. adapter_model.safetensors +1 -1
  3. runs/Mar04_23-36-40_b2f1c2a0054d/events.out.tfevents.1709595402.b2f1c2a0054d.1093.1 +3 -0
  4. 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-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the generator dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5225
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  ## Model description
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@@ -44,7 +44,7 @@ The following hyperparameters were used during training:
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  - eval_batch_size: 8
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  - seed: 42
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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: 3
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  - training_steps: 200
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@@ -52,14 +52,14 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 1.6742 | 0.03 | 25 | 1.6357 |
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- | 1.5587 | 0.05 | 50 | 1.5519 |
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- | 1.5001 | 0.08 | 75 | 1.5390 |
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- | 1.5723 | 0.11 | 100 | 1.5331 |
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- | 1.4801 | 0.13 | 125 | 1.5288 |
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- | 1.5756 | 0.16 | 150 | 1.5269 |
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- | 1.4888 | 0.19 | 175 | 1.5251 |
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- | 1.5356 | 0.22 | 200 | 1.5225 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the generator dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.5221
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  ## Model description
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  - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_steps: 3
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  - training_steps: 200
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.6694 | 0.03 | 25 | 1.6401 |
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+ | 1.5146 | 0.05 | 50 | 1.5519 |
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+ | 1.5803 | 0.08 | 75 | 1.5408 |
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+ | 1.5458 | 0.11 | 100 | 1.5345 |
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+ | 1.4207 | 0.13 | 125 | 1.5274 |
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+ | 1.5952 | 0.16 | 150 | 1.5242 |
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+ | 1.5299 | 0.19 | 175 | 1.5224 |
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+ | 1.5765 | 0.22 | 200 | 1.5221 |
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  ### Framework versions
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