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End of training

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  1. README.md +15 -9
  2. model.safetensors +1 -1
  3. training_args.bin +2 -2
README.md CHANGED
@@ -1,8 +1,8 @@
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  ---
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  license: other
 
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  tags:
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  - generated_from_trainer
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- base_model: facebook/opt-125m
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  model-index:
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  - name: opt125_wiki_ce
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  results: []
@@ -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 [facebook/opt-125m](https://huggingface.co/facebook/opt-125m) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.9865
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  ## Model description
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@@ -34,19 +34,25 @@ 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: 16
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- - eval_batch_size: 64
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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: linear
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- - num_epochs: 1
 
 
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:-----:|:----:|:---------------:|
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- | 3.194 | 1.0 | 1200 | 2.9865 |
 
 
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  ### Framework versions
 
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  ---
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  license: other
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+ base_model: facebook/opt-125m
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  tags:
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  - generated_from_trainer
 
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  model-index:
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  - name: opt125_wiki_ce
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  results: []
 
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  This model is a fine-tuned version of [facebook/opt-125m](https://huggingface.co/facebook/opt-125m) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.8236
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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: 1e-05
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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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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 16
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 3
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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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+ | 3.1211 | 0.8340 | 500 | 2.8961 |
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+ | 2.9653 | 1.6681 | 1000 | 2.8385 |
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+ | 2.8971 | 2.5021 | 1500 | 2.8258 |
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  ### Framework versions
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