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HybridModelScratch_2

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Safetensors
hybrid_fourier_lm
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  1. README.md +7 -15
  2. best_model_streaming/model.safetensors +1 -1
  3. best_model_streaming/training_args.bin +1 -1
README.md CHANGED
@@ -5,19 +5,19 @@ tags:
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  metrics:
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  - accuracy
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  model-index:
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- - name: HybridModelScratch_
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # HybridModelScratch_
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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: 5.2920
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- - Accuracy: 0.2203
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  ## Model description
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@@ -36,7 +36,7 @@ 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: 0.0001
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  - train_batch_size: 64
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  - eval_batch_size: 16
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  - seed: 42
@@ -51,16 +51,8 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 32.0977 | 0.1 | 100 | 7.3025 | 0.1141 |
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- | 26.0238 | 0.2 | 200 | 6.3336 | 0.1618 |
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- | 24.2338 | 0.3 | 300 | 5.9560 | 0.1830 |
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- | 23.2729 | 0.4 | 400 | 5.7180 | 0.1967 |
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- | 22.5651 | 0.5 | 500 | 5.5544 | 0.2059 |
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- | 22.0473 | 0.6 | 600 | 5.4359 | 0.2119 |
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- | 21.7227 | 0.7 | 700 | 5.3620 | 0.2162 |
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- | 21.4768 | 0.8 | 800 | 5.3150 | 0.2189 |
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- | 21.3548 | 0.9 | 900 | 5.2958 | 0.2200 |
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- | 21.3675 | 1.0 | 1000 | 5.2920 | 0.2203 |
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  ### Framework versions
 
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  metrics:
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  - accuracy
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  model-index:
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+ - name: HybridModelScratch_2
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ # HybridModelScratch_2
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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: 3.9696
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+ - Accuracy: 0.3206
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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: 0.001
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  - train_batch_size: 64
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  - eval_batch_size: 16
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 17.8605 | 0.5 | 500 | 4.3490 | 0.2816 |
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+ | 16.0566 | 1.0 | 1000 | 3.9696 | 0.3206 |
 
 
 
 
 
 
 
 
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  ### Framework versions
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