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mtzig
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maze_replicate_10_test

Transformers
Safetensors
nanogpt
Generated from Trainer
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  1. README.md +13 -5
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -2,6 +2,8 @@
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  library_name: transformers
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: maze_replicate_10_test
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  results: []
@@ -13,6 +15,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # maze_replicate_10_test
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
 
 
 
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.001
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- - train_batch_size: 128
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  - eval_batch_size: 128
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  - seed: 7658372
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  - gradient_accumulation_steps: 2
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- - total_train_batch_size: 256
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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: cosine
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  - lr_scheduler_warmup_ratio: 0.1
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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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- | No log | 0 | 0 | 1.8216 | 0.0 |
 
 
 
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  ### Framework versions
 
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  library_name: transformers
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  tags:
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  - generated_from_trainer
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+ metrics:
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+ - accuracy
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  model-index:
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  - name: maze_replicate_10_test
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  results: []
 
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  # maze_replicate_10_test
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.6046
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+ - Accuracy: 0.0
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.001
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+ - train_batch_size: 32
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  - eval_batch_size: 128
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  - seed: 7658372
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  - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 64
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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: cosine
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  - lr_scheduler_warmup_ratio: 0.1
 
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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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+ | No log | 0 | 0 | 1.8580 | 0.0 |
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+ | 3.4351 | 0.3175 | 10 | 1.6489 | 0.0 |
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+ | 3.3558 | 0.6349 | 20 | 1.6199 | 0.0 |
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+ | 3.3084 | 0.9524 | 30 | 1.6046 | 0.0 |
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  ### Framework versions
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