asr-nigerian-pidgin
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pidgin-wav2vec2-xlsr53

@@ -1,201 +1,83 @@
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 ---
+license: apache-2.0
+base_model: facebook/wav2vec2-large-xlsr-53
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: pidgin-wav2vec2-xlsr53
+  results: []
 ---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# pidgin-wav2vec2-xlsr53
+This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the Nigerian Pidgin dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6907
+- Wer: 0.3161 (val)
+## Model description
+*to be updated*
+## Intended uses & limitations
+*to be updated*
+## Training and evaluation data
+*to be updated*
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 3407
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 1000
+- num_epochs: 30
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch | Step  | Validation Loss | Wer    |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|
+| 6.604         | 1.48  | 500   | 3.0540          | 1.0    |
+| 3.0176        | 2.95  | 1000  | 3.0035          | 1.0    |
+| 2.1071        | 4.43  | 1500  | 1.0811          | 0.6289 |
+| 1.1143        | 5.91  | 2000  | 0.8348          | 0.5017 |
+| 0.8501        | 7.39  | 2500  | 0.7707          | 0.4352 |
+| 0.7272        | 8.86  | 3000  | 0.7410          | 0.4075 |
+| 0.6038        | 10.34 | 3500  | 0.6283          | 0.3850 |
+| 0.5334        | 11.82 | 4000  | 0.6356          | 0.3701 |
+| 0.4645        | 13.29 | 4500  | 0.6243          | 0.3657 |
+| 0.4251        | 14.77 | 5000  | 0.6838          | 0.3492 |
+| 0.3801        | 16.25 | 5500  | 0.6619          | 0.3445 |
+| 0.3636        | 17.73 | 6000  | 0.6945          | 0.3360 |
+| 0.3366        | 19.2  | 6500  | 0.6108          | 0.3340 |
+| 0.3146        | 20.68 | 7000  | 0.6511          | 0.3273 |
+| 0.3003        | 22.16 | 7500  | 0.6815          | 0.3253 |
+| 0.2783        | 23.63 | 8000  | 0.6761          | 0.3215 |
+| 0.2601        | 25.11 | 8500  | 0.6762          | 0.3187 |
+| 0.2528        | 26.59 | 9000  | 0.6687          | 0.3194 |
+| 0.2409        | 28.06 | 9500  | 0.7064          | 0.3163 |
+| 0.2359        | 29.54 | 10000 | 0.6907          | 0.3161 |
+### Framework versions
+- Transformers 4.37.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.12.0
+- Tokenizers 0.15.2