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--- |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-1b-all |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: mms-1b-all-lg-CV-Fleurs_filtered-100hrs-v1 |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: fleurs |
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type: fleurs |
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config: lg_ug |
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split: test |
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args: lg_ug |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.4098153547133139 |
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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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# mms-1b-all-lg-CV-Fleurs_filtered-100hrs-v1 |
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2897 |
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- Wer: 0.4098 |
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- Cer: 0.0743 |
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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: 0.001 |
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- train_batch_size: 4 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Use 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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- num_epochs: 70 |
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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 | Wer | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
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| 0.3203 | 1.0 | 7125 | 0.3178 | 0.4156 | 0.0762 | |
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| 0.2149 | 2.0 | 14250 | 0.3008 | 0.4194 | 0.0759 | |
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| 0.2093 | 3.0 | 21375 | 0.3015 | 0.4017 | 0.0743 | |
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| 0.2064 | 4.0 | 28500 | 0.3043 | 0.4114 | 0.0745 | |
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| 0.2042 | 5.0 | 35625 | 0.2955 | 0.4069 | 0.0753 | |
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| 0.2022 | 6.0 | 42750 | 0.3009 | 0.4088 | 0.0750 | |
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| 0.1989 | 7.0 | 49875 | 0.3088 | 0.4092 | 0.0756 | |
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| 0.1983 | 8.0 | 57000 | 0.2980 | 0.4081 | 0.0754 | |
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| 0.1969 | 9.0 | 64125 | 0.2951 | 0.4040 | 0.0741 | |
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| 0.1957 | 10.0 | 71250 | 0.2899 | 0.4039 | 0.0745 | |
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| 0.1945 | 11.0 | 78375 | 0.2896 | 0.4083 | 0.0744 | |
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| 0.1936 | 12.0 | 85500 | 0.2931 | 0.4038 | 0.0743 | |
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| 0.1929 | 13.0 | 92625 | 0.2897 | 0.4098 | 0.0743 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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