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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-coraa-exp-11
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. -->
# wav2vec2-large-xlsr-coraa-exp-11
This model is a fine-tuned version of [Edresson/wav2vec2-large-xlsr-coraa-portuguese](https://huggingface.co/Edresson/wav2vec2-large-xlsr-coraa-portuguese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 8.9926
- Wer: 0.9866
- Cer: 0.9323
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 150
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 38.5161 | 1.0 | 14 | 34.2489 | 1.0 | 0.9510 |
| 38.5161 | 2.0 | 28 | 23.3869 | 1.0 | 0.9510 |
| 38.5161 | 3.0 | 42 | 19.6721 | 1.0 | 0.9510 |
| 38.5161 | 4.0 | 56 | 18.3735 | 1.0 | 0.9510 |
| 38.5161 | 5.0 | 70 | 17.5507 | 1.0026 | 0.9496 |
| 38.5161 | 6.0 | 84 | 16.9340 | 1.0738 | 0.9688 |
| 38.5161 | 7.0 | 98 | 17.3229 | 1.0004 | 0.9511 |
| 17.5323 | 8.0 | 112 | 16.4594 | 1.0156 | 0.9314 |
| 17.5323 | 9.0 | 126 | 12.4451 | 1.0299 | 0.9352 |
| 17.5323 | 10.0 | 140 | 10.0922 | 1.0 | 0.9619 |
| 17.5323 | 11.0 | 154 | 9.5186 | 0.9998 | 0.9618 |
| 17.5323 | 12.0 | 168 | 8.9926 | 0.9866 | 0.9323 |
| 17.5323 | 13.0 | 182 | 9.0185 | 0.9839 | 0.9167 |
| 17.5323 | 14.0 | 196 | 9.1242 | 0.9837 | 0.9216 |
| 6.6506 | 15.0 | 210 | 9.0501 | 0.9880 | 0.8844 |
| 6.6506 | 16.0 | 224 | 9.1892 | 0.9777 | 0.9022 |
| 6.6506 | 17.0 | 238 | 9.1733 | 0.9799 | 0.8847 |
| 6.6506 | 18.0 | 252 | 9.3033 | 0.9799 | 0.8733 |
| 6.6506 | 19.0 | 266 | 9.2853 | 0.9746 | 0.8990 |
| 6.6506 | 20.0 | 280 | 9.4380 | 0.9748 | 0.9086 |
| 6.6506 | 21.0 | 294 | 9.5132 | 0.9750 | 0.8900 |
| 3.6568 | 22.0 | 308 | 9.6268 | 0.9817 | 0.8811 |
| 3.6568 | 23.0 | 322 | 9.6989 | 1.0043 | 0.8847 |
| 3.6568 | 24.0 | 336 | 9.6113 | 0.9789 | 0.8963 |
| 3.6568 | 25.0 | 350 | 9.7947 | 0.9807 | 0.8924 |
| 3.6568 | 26.0 | 364 | 9.8381 | 0.9795 | 0.8979 |
| 3.6568 | 27.0 | 378 | 10.0306 | 0.9789 | 0.8952 |
| 3.6568 | 28.0 | 392 | 9.9950 | 0.9793 | 0.8947 |
| 3.316 | 29.0 | 406 | 10.1488 | 0.9781 | 0.8979 |
| 3.316 | 30.0 | 420 | 10.1934 | 0.9809 | 0.9092 |
| 3.316 | 31.0 | 434 | 10.2146 | 0.9880 | 0.9299 |
| 3.316 | 32.0 | 448 | 10.2985 | 0.9998 | 0.9593 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.13.3
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