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End of training

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  1. README.md +10 -9
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [ad019el/tamasheq-99-1](https://huggingface.co/ad019el/tamasheq-99-1) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3479
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- - Wer: 0.4957
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  ## Model description
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@@ -46,22 +46,23 @@ The following hyperparameters were used during training:
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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: 30
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 4.3118 | 6.0 | 300 | 0.8477 | 0.8593 |
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- | 0.4823 | 12.0 | 600 | 0.3741 | 0.5064 |
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- | 0.2054 | 18.0 | 900 | 0.3855 | 0.5027 |
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- | 0.1798 | 24.0 | 1200 | 0.3700 | 0.5023 |
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- | 0.2097 | 30.0 | 1500 | 0.3479 | 0.4957 |
 
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  ### Framework versions
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- - Transformers 4.31.0
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.4
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  - Tokenizers 0.13.3
 
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  This model is a fine-tuned version of [ad019el/tamasheq-99-1](https://huggingface.co/ad019el/tamasheq-99-1) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.3783
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+ - Wer: 0.8147
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  ## Model description
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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: 200
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 7.9063 | 7.89 | 300 | 3.0656 | 1.0 |
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+ | 2.7952 | 15.79 | 600 | 1.7388 | 0.9324 |
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+ | 1.2354 | 23.68 | 900 | 1.0927 | 0.8618 |
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+ | 0.8131 | 31.58 | 1200 | 1.1919 | 0.8618 |
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+ | 0.6311 | 39.47 | 1500 | 1.2800 | 0.8559 |
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+ | 0.5422 | 47.37 | 1800 | 1.3783 | 0.8147 |
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  ### Framework versions
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+ - Transformers 4.32.1
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.4
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  - Tokenizers 0.13.3
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