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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: mms-meta/mms-zeroshot-300m |
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tags: |
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- automatic-speech-recognition |
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- genbed |
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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-zeroshot-300m-genbed-f-model |
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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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# mms-zeroshot-300m-genbed-f-model |
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This model is a fine-tuned version of [mms-meta/mms-zeroshot-300m](https://huggingface.co/mms-meta/mms-zeroshot-300m) on the GENBED - BEM dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2100 |
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- Wer: 0.3721 |
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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: 0.0003 |
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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: 100 |
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- num_epochs: 30.0 |
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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 | 0.5479 | 200 | 2.3236 | 1.0 | |
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| No log | 1.0959 | 400 | 0.3331 | 0.5504 | |
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| 2.6731 | 1.6438 | 600 | 0.2969 | 0.5190 | |
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| 2.6731 | 2.1918 | 800 | 0.2806 | 0.5122 | |
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| 0.4193 | 2.7397 | 1000 | 0.2701 | 0.4742 | |
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| 0.4193 | 3.2877 | 1200 | 0.2703 | 0.4770 | |
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| 0.4193 | 3.8356 | 1400 | 0.2574 | 0.4758 | |
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| 0.367 | 4.3836 | 1600 | 0.2487 | 0.4547 | |
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| 0.367 | 4.9315 | 1800 | 0.2472 | 0.4337 | |
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| 0.3377 | 5.4795 | 2000 | 0.2424 | 0.4467 | |
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| 0.3377 | 6.0274 | 2200 | 0.2372 | 0.4274 | |
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| 0.3377 | 6.5753 | 2400 | 0.2366 | 0.4225 | |
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| 0.3282 | 7.1233 | 2600 | 0.2339 | 0.4104 | |
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| 0.3282 | 7.6712 | 2800 | 0.2352 | 0.4193 | |
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| 0.3018 | 8.2192 | 3000 | 0.2249 | 0.4097 | |
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| 0.3018 | 8.7671 | 3200 | 0.2254 | 0.4065 | |
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| 0.3018 | 9.3151 | 3400 | 0.2251 | 0.4021 | |
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| 0.2945 | 9.8630 | 3600 | 0.2248 | 0.3969 | |
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| 0.2945 | 10.4110 | 3800 | 0.2212 | 0.4002 | |
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| 0.2843 | 10.9589 | 4000 | 0.2200 | 0.3920 | |
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| 0.2843 | 11.5068 | 4200 | 0.2183 | 0.3853 | |
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| 0.2843 | 12.0548 | 4400 | 0.2174 | 0.3890 | |
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| 0.2755 | 12.6027 | 4600 | 0.2163 | 0.3955 | |
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| 0.2755 | 13.1507 | 4800 | 0.2197 | 0.3894 | |
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| 0.2699 | 13.6986 | 5000 | 0.2163 | 0.3899 | |
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| 0.2699 | 14.2466 | 5200 | 0.2129 | 0.3769 | |
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| 0.2699 | 14.7945 | 5400 | 0.2114 | 0.3759 | |
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| 0.2568 | 15.3425 | 5600 | 0.2100 | 0.3721 | |
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| 0.2568 | 15.8904 | 5800 | 0.2140 | 0.3670 | |
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| 0.2521 | 16.4384 | 6000 | 0.2149 | 0.3743 | |
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| 0.2521 | 16.9863 | 6200 | 0.2131 | 0.3720 | |
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### Framework versions |
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- Transformers 4.46.0.dev0 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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