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fine_tuned_all_domains_balanced_1.5

Text Classification
Transformers
Safetensors
qwen2
Generated from Trainer
text-generation-inference
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qwen_new_mage_all_domains_balanced_1.5

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  1. README.md +13 -11
  2. evaluation_results.json +8 -0
  3. model-00001-of-00002.safetensors +1 -1
  4. model-00002-of-00002.safetensors +1 -1
  5. training_args.bin +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [Qwen/Qwen1.5-1.8B](https://huggingface.co/Qwen/Qwen1.5-1.8B) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2426
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- - Accuracy: 0.9020
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  ## Model description
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@@ -38,25 +38,27 @@ 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: 2e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | 0.7734 | 0.0172 | 100 | 0.3509 | 0.8435 |
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- | 0.4233 | 0.0344 | 200 | 0.6423 | 0.7446 |
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- | 0.349 | 0.0516 | 300 | 0.3206 | 0.8669 |
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- | 0.2886 | 0.0688 | 400 | 0.2244 | 0.9020 |
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- | 0.2777 | 0.0860 | 500 | 0.6114 | 0.7797 |
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- | 0.246 | 0.1032 | 600 | 0.3122 | 0.8723 |
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- | 0.2295 | 0.1204 | 700 | 0.2426 | 0.9020 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [Qwen/Qwen1.5-1.8B](https://huggingface.co/Qwen/Qwen1.5-1.8B) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1147
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+ - Accuracy: 0.9703
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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: 5e-06
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - num_epochs: 1
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.1945 | 0.0860 | 500 | 0.4187 | 0.8732 |
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+ | 0.171 | 0.1720 | 1000 | 0.1541 | 0.9371 |
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+ | 0.1235 | 0.2580 | 1500 | 0.1469 | 0.9451 |
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+ | 0.1233 | 0.3441 | 2000 | 0.1433 | 0.9532 |
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+ | 0.1109 | 0.4301 | 2500 | 0.1395 | 0.9541 |
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+ | 0.108 | 0.5161 | 3000 | 0.1134 | 0.9622 |
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+ | 0.0864 | 0.6021 | 3500 | 0.1452 | 0.9649 |
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+ | 0.0743 | 0.6881 | 4000 | 0.1336 | 0.9676 |
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+ | 0.0637 | 0.7741 | 4500 | 0.1147 | 0.9703 |
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  ### Framework versions
evaluation_results.json ADDED
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+ {
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+ "eval_loss": 0.24256853759288788,
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+ "eval_accuracy": 0.9019784172661871,
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+ "eval_runtime": 35.5314,
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+ "eval_samples_per_second": 31.296,
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+ "eval_steps_per_second": 0.985,
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+ "epoch": 0.12041974883880957
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+ }
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