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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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base_model: facebook/wav2vec2-xls-r-300m |
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datasets: |
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- ml-superb-subset |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-ml-superb-xty |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: ml-superb-subset |
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type: ml-superb-subset |
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config: xty |
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split: test |
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args: xty |
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metrics: |
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- type: wer |
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value: 0.8114393463230672 |
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name: Wer |
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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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# wav2vec2-large-xls-r-300m-ml-superb-xty |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the ml-superb-subset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6099 |
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- Wer: 0.8114 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 30 |
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- num_epochs: 10 |
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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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| 3.1825 | 0.8219 | 30 | 3.2071 | 1.0 | |
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| 3.0491 | 1.6438 | 60 | 3.0508 | 1.0 | |
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| 2.9717 | 2.4658 | 90 | 3.0385 | 1.0 | |
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| 2.93 | 3.2877 | 120 | 2.9222 | 1.0 | |
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| 2.6444 | 4.1096 | 150 | 2.3753 | 0.9931 | |
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| 2.05 | 4.9315 | 180 | 1.9591 | 0.9868 | |
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| 1.6856 | 5.7534 | 210 | 1.7810 | 0.9478 | |
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| 1.4182 | 6.5753 | 240 | 1.6843 | 0.8843 | |
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| 1.1773 | 7.3973 | 270 | 1.6370 | 0.8554 | |
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| 1.0521 | 8.2192 | 300 | 1.5868 | 0.8215 | |
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| 0.881 | 9.0411 | 330 | 1.5935 | 0.8202 | |
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| 0.7605 | 9.8630 | 360 | 1.6099 | 0.8114 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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