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--- |
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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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- automatic-speech-recognition |
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- BembaSpeech |
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- mms |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: mms-1b-bem-female-sv |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/cicasote/huggingface/runs/tuxgh6td) |
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# mms-1b-bem-female-sv |
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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 BEMBASPEECH - BEM dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2132 |
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- Wer: 0.3557 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 5.0 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| No log | 0.3992 | 200 | 0.3566 | 0.5019 | |
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| No log | 0.7984 | 400 | 0.2620 | 0.4029 | |
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| 1.7214 | 1.1976 | 600 | 0.2546 | 0.4100 | |
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| 1.7214 | 1.5968 | 800 | 0.2359 | 0.3965 | |
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| 0.2801 | 1.9960 | 1000 | 0.2322 | 0.3810 | |
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| 0.2801 | 2.3952 | 1200 | 0.2305 | 0.3746 | |
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| 0.2801 | 2.7944 | 1400 | 0.2258 | 0.3336 | |
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| 0.2528 | 3.1936 | 1600 | 0.2262 | 0.4309 | |
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| 0.2528 | 3.5928 | 1800 | 0.2164 | 0.3514 | |
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| 0.2351 | 3.9920 | 2000 | 0.2215 | 0.3894 | |
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| 0.2351 | 4.3912 | 2200 | 0.2165 | 0.3624 | |
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| 0.2351 | 4.7904 | 2400 | 0.2132 | 0.3557 | |
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### Framework versions |
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- Transformers 4.43.0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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