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fine_tuned_all_domains_1.5

Text Classification
Transformers
Safetensors
qwen2
Generated from Trainer
text-generation-inference
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Arihant Tripathi commited on
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qwen_new_mage_all_domains_1.5

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Files changed (5) hide show
  1. README.md +20 -13
  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: 0.2369
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- - Accuracy: 0.9083
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  ## Model description
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@@ -38,25 +38,32 @@ 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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- | 0.6318 | 0.0101 | 100 | 0.4632 | 0.8561 |
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- | 0.3263 | 0.0201 | 200 | 0.2369 | 0.9029 |
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- | 0.313 | 0.0302 | 300 | 0.3302 | 0.8813 |
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- | 0.2693 | 0.0403 | 400 | 0.2005 | 0.9083 |
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- | 0.2409 | 0.0503 | 500 | 0.2083 | 0.8993 |
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- | 0.229 | 0.0604 | 600 | 0.2315 | 0.9011 |
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- | 0.2413 | 0.0704 | 700 | 0.2369 | 0.9083 |
 
 
 
 
 
 
 
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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: 0.2531
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+ - Accuracy: 0.9460
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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: 8
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+ - eval_batch_size: 8
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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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+ | 0.4234 | 0.0126 | 500 | 0.3614 | 0.8957 |
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+ | 0.2949 | 0.0252 | 1000 | 0.2974 | 0.9101 |
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+ | 0.3592 | 0.0377 | 1500 | 0.2913 | 0.9137 |
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+ | 0.3101 | 0.0503 | 2000 | 0.2877 | 0.9326 |
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+ | 0.2923 | 0.0629 | 2500 | 0.2246 | 0.9290 |
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+ | 0.2778 | 0.0755 | 3000 | 0.2472 | 0.9397 |
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+ | 0.2556 | 0.0881 | 3500 | 0.2163 | 0.9487 |
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+ | 0.2986 | 0.1006 | 4000 | 0.2156 | 0.9478 |
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+ | 0.272 | 0.1132 | 4500 | 0.2387 | 0.9388 |
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+ | 0.2363 | 0.1258 | 5000 | 0.4263 | 0.9326 |
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+ | 0.221 | 0.1384 | 5500 | 0.2054 | 0.9505 |
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+ | 0.2478 | 0.1510 | 6000 | 0.2851 | 0.9451 |
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+ | 0.2451 | 0.1635 | 6500 | 0.2730 | 0.9442 |
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+ | 0.1915 | 0.1761 | 7000 | 0.2531 | 0.9460 |
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  ### Framework versions
evaluation_results.json ADDED
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+ {
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+ "eval_loss": 0.2368740439414978,
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+ "eval_accuracy": 0.908273381294964,
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+ "eval_runtime": 28.8018,
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+ "eval_samples_per_second": 38.609,
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+ "eval_steps_per_second": 1.215,
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+ "epoch": 0.07044379591425984
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+ }
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