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update model card README.md
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README.md
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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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datasets:
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- common_voice
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model-index:
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- name: wav2vec2-large-xls-r-300m-spanish-large
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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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# wav2vec2-large-xls-r-300m-spanish-large
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This model is a fine-tuned version of [tomascufaro/xls-r-es-test](https://huggingface.co/tomascufaro/xls-r-es-test) on the common_voice dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1431
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- Wer: 0.1197
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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: 0.0002
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- train_batch_size: 10
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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: 20
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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: 300
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- num_epochs: 5
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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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| 0.1769 | 0.15 | 400 | 0.1795 | 0.1698 |
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| 0.217 | 0.3 | 800 | 0.2000 | 0.1945 |
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| 0.2372 | 0.45 | 1200 | 0.1985 | 0.1859 |
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| 0.2351 | 0.6 | 1600 | 0.1901 | 0.1772 |
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| 0.2269 | 0.75 | 2000 | 0.1968 | 0.1783 |
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| 0.2284 | 0.9 | 2400 | 0.1873 | 0.1771 |
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| 0.2014 | 1.06 | 2800 | 0.1840 | 0.1696 |
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| 0.1988 | 1.21 | 3200 | 0.1904 | 0.1730 |
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| 0.1919 | 1.36 | 3600 | 0.1827 | 0.1630 |
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| 0.1919 | 1.51 | 4000 | 0.1788 | 0.1629 |
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| 0.1817 | 1.66 | 4400 | 0.1755 | 0.1558 |
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| 0.1812 | 1.81 | 4800 | 0.1795 | 0.1638 |
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| 0.1808 | 1.96 | 5200 | 0.1762 | 0.1603 |
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| 0.1625 | 2.11 | 5600 | 0.1721 | 0.1557 |
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| 0.1477 | 2.26 | 6000 | 0.1735 | 0.1504 |
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| 0.1508 | 2.41 | 6400 | 0.1708 | 0.1478 |
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| 0.157 | 2.56 | 6800 | 0.1644 | 0.1466 |
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| 0.1491 | 2.71 | 7200 | 0.1638 | 0.1445 |
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| 0.1458 | 2.86 | 7600 | 0.1582 | 0.1426 |
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| 0.1387 | 3.02 | 8000 | 0.1607 | 0.1376 |
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| 0.1269 | 3.17 | 8400 | 0.1559 | 0.1364 |
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| 0.1172 | 3.32 | 8800 | 0.1521 | 0.1335 |
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| 0.1203 | 3.47 | 9200 | 0.1534 | 0.1330 |
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| 0.1177 | 3.62 | 9600 | 0.1485 | 0.1304 |
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| 0.1167 | 3.77 | 10000 | 0.1498 | 0.1302 |
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| 0.1194 | 3.92 | 10400 | 0.1463 | 0.1287 |
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| 0.1053 | 4.07 | 10800 | 0.1483 | 0.1282 |
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| 0.098 | 4.22 | 11200 | 0.1498 | 0.1267 |
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| 0.0958 | 4.37 | 11600 | 0.1461 | 0.1233 |
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| 0.0946 | 4.52 | 12000 | 0.1444 | 0.1218 |
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| 0.094 | 4.67 | 12400 | 0.1434 | 0.1206 |
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| 0.0932 | 4.82 | 12800 | 0.1424 | 0.1206 |
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| 0.0912 | 4.98 | 13200 | 0.1431 | 0.1197 |
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### Framework versions
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- Transformers 4.17.0.dev0
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- Pytorch 1.10.2+cu102
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- Datasets 1.18.2.dev0
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- Tokenizers 0.11.0
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