End of training
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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: arbml/whisper-small-ar
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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: whisper-small-ar-eos-v6-mulaw
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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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# whisper-small-ar-eos-v6-mulaw
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This model is a fine-tuned version of [arbml/whisper-small-ar](https://huggingface.co/arbml/whisper-small-ar) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7786
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- Accuracy: 0.7073
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-07
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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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: linear
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 30
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- mixed_precision_training: Native AMP
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- label_smoothing_factor: 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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| 0.8494 | 1.0 | 557 | 0.8372 | 0.5987 |
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| 0.7418 | 2.0 | 1114 | 0.7249 | 0.7012 |
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| 0.7201 | 3.0 | 1671 | 0.7034 | 0.7144 |
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| 0.7032 | 4.0 | 2228 | 0.6996 | 0.7123 |
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| 0.7016 | 5.0 | 2785 | 0.6956 | 0.7169 |
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| 0.64 | 6.0 | 3342 | 0.7002 | 0.7184 |
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| 0.6507 | 7.0 | 3899 | 0.6937 | 0.7245 |
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| 0.6972 | 8.0 | 4456 | 0.6966 | 0.7235 |
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| 0.6435 | 9.0 | 5013 | 0.6954 | 0.7260 |
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| 0.6437 | 10.0 | 5570 | 0.6969 | 0.7194 |
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| 0.675 | 11.0 | 6127 | 0.7022 | 0.7225 |
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| 0.6486 | 12.0 | 6684 | 0.7024 | 0.7220 |
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| 0.5699 | 13.0 | 7241 | 0.7103 | 0.7199 |
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| 0.6024 | 14.0 | 7798 | 0.7070 | 0.7220 |
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| 0.6019 | 15.0 | 8355 | 0.7145 | 0.7220 |
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| 0.6209 | 16.0 | 8912 | 0.7201 | 0.7230 |
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| 0.5811 | 17.0 | 9469 | 0.7241 | 0.7210 |
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| 0.5941 | 18.0 | 10026 | 0.7281 | 0.7199 |
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| 0.5847 | 19.0 | 10583 | 0.7371 | 0.7210 |
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| 0.5309 | 20.0 | 11140 | 0.7435 | 0.7098 |
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| 0.5697 | 21.0 | 11697 | 0.7490 | 0.7128 |
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| 0.5536 | 22.0 | 12254 | 0.7534 | 0.7103 |
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| 0.5517 | 23.0 | 12811 | 0.7636 | 0.7118 |
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| 0.5907 | 24.0 | 13368 | 0.7624 | 0.7123 |
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| 0.5081 | 25.0 | 13925 | 0.7674 | 0.7103 |
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| 0.5305 | 26.0 | 14482 | 0.7706 | 0.7103 |
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| 0.4848 | 27.0 | 15039 | 0.7740 | 0.7083 |
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| 0.4801 | 28.0 | 15596 | 0.7761 | 0.7093 |
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| 0.5059 | 29.0 | 16153 | 0.7776 | 0.7042 |
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| 0.51 | 30.0 | 16710 | 0.7786 | 0.7073 |
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### Framework versions
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- Transformers 4.49.0.dev0
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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model.safetensors
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runs/Feb13_15-47-56_42d6640966bb/events.out.tfevents.1739461679.42d6640966bb.30654.0
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