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testts1234

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  1. README.md +37 -17
  2. model.safetensors +1 -1
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [fahadqazi/testts1234](https://huggingface.co/fahadqazi/testts1234) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3292
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  ## Model description
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@@ -34,30 +34,50 @@ 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: 2.53e-05
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  - train_batch_size: 64
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  - eval_batch_size: 100
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  - seed: 42
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  - optimizer: Use 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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- - lr_scheduler_warmup_steps: 1000
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- - training_steps: 5000
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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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- | 0.3551 | 1.9231 | 500 | 0.3307 |
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- | 0.3621 | 3.8462 | 1000 | 0.3360 |
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- | 0.363 | 5.7692 | 1500 | 0.3327 |
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- | 0.3637 | 7.6923 | 2000 | 0.3326 |
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- | 0.3606 | 9.6154 | 2500 | 0.3314 |
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- | 0.3595 | 11.5385 | 3000 | 0.3306 |
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- | 0.3594 | 13.4615 | 3500 | 0.3307 |
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- | 0.3594 | 15.3846 | 4000 | 0.3296 |
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- | 0.3602 | 17.3077 | 4500 | 0.3294 |
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- | 0.3577 | 19.2308 | 5000 | 0.3292 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [fahadqazi/testts1234](https://huggingface.co/fahadqazi/testts1234) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3178
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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-05
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  - train_batch_size: 64
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  - eval_batch_size: 100
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  - seed: 42
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  - optimizer: Use 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: cosine
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+ - lr_scheduler_warmup_steps: 100
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+ - training_steps: 30000
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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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+ | 0.373 | 3.8462 | 1000 | 0.3301 |
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+ | 0.3754 | 7.6923 | 2000 | 0.3296 |
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+ | 0.3769 | 11.5385 | 3000 | 0.3330 |
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+ | 0.3756 | 15.3846 | 4000 | 0.3265 |
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+ | 0.3731 | 19.2308 | 5000 | 0.3290 |
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+ | 0.3722 | 23.0769 | 6000 | 0.3285 |
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+ | 0.3723 | 26.9231 | 7000 | 0.3290 |
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+ | 0.3725 | 30.7692 | 8000 | 0.3284 |
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+ | 0.3732 | 34.6154 | 9000 | 0.3264 |
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+ | 0.3692 | 38.4615 | 10000 | 0.3326 |
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+ | 0.3667 | 42.3077 | 11000 | 0.3256 |
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+ | 0.3667 | 46.1538 | 12000 | 0.3267 |
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+ | 0.3675 | 50.0 | 13000 | 0.3248 |
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+ | 0.3634 | 53.8462 | 14000 | 0.3229 |
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+ | 0.3613 | 57.6923 | 15000 | 0.3236 |
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+ | 0.3612 | 61.5385 | 16000 | 0.3215 |
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+ | 0.3606 | 65.3846 | 17000 | 0.3218 |
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+ | 0.363 | 69.2308 | 18000 | 0.3212 |
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+ | 0.3592 | 73.0769 | 19000 | 0.3202 |
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+ | 0.3598 | 76.9231 | 20000 | 0.3202 |
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+ | 0.3568 | 80.7692 | 21000 | 0.3192 |
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+ | 0.3558 | 84.6154 | 22000 | 0.3194 |
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+ | 0.3553 | 88.4615 | 23000 | 0.3188 |
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+ | 0.356 | 92.3077 | 24000 | 0.3184 |
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+ | 0.3562 | 96.1538 | 25000 | 0.3184 |
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+ | 0.3552 | 100.0 | 26000 | 0.3181 |
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+ | 0.3521 | 103.8462 | 27000 | 0.3175 |
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+ | 0.3542 | 107.6923 | 28000 | 0.3181 |
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+ | 0.3569 | 111.5385 | 29000 | 0.3178 |
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+ | 0.3539 | 115.3846 | 30000 | 0.3178 |
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  ### Framework versions
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