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---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- DewiBrynJones/banc-trawsgrifiadau-bangor-normalized
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-ft-btb-cy
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-xlsr-53-ft-btb-cy
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the DEWIBRYNJONES/BANC-TRAWSGRIFIADAU-BANGOR-NORMALIZED - DEFAULT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4086
- Wer: 0.3122
## 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: 0.0003
- 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
- lr_scheduler_warmup_steps: 500
- training_steps: 2600
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log | 0.1414 | 100 | 3.6264 | 1.0 |
| No log | 0.2829 | 200 | 3.1080 | 1.0 |
| No log | 0.4243 | 300 | 2.5440 | 0.9863 |
| No log | 0.5658 | 400 | 1.2381 | 0.8110 |
| 3.4586 | 0.7072 | 500 | 1.0036 | 0.7184 |
| 3.4586 | 0.8487 | 600 | 0.8524 | 0.6379 |
| 3.4586 | 0.9901 | 700 | 0.7411 | 0.5673 |
| 3.4586 | 1.1315 | 800 | 0.6203 | 0.4838 |
| 3.4586 | 1.2730 | 900 | 0.6017 | 0.4820 |
| 0.8146 | 1.4144 | 1000 | 0.5637 | 0.4462 |
| 0.8146 | 1.5559 | 1100 | 0.5381 | 0.4208 |
| 0.8146 | 1.6973 | 1200 | 0.5155 | 0.4043 |
| 0.8146 | 1.8388 | 1300 | 0.4858 | 0.3903 |
| 0.8146 | 1.9802 | 1400 | 0.4758 | 0.3823 |
| 0.6294 | 2.1216 | 1500 | 0.4604 | 0.3642 |
| 0.6294 | 2.2631 | 1600 | 0.4531 | 0.3536 |
| 0.6294 | 2.4045 | 1700 | 0.4435 | 0.3511 |
| 0.6294 | 2.5460 | 1800 | 0.4366 | 0.3499 |
| 0.6294 | 2.6874 | 1900 | 0.4309 | 0.3451 |
| 0.4914 | 2.8289 | 2000 | 0.4252 | 0.3368 |
| 0.4914 | 2.9703 | 2100 | 0.4218 | 0.3285 |
| 0.4914 | 3.1117 | 2200 | 0.4208 | 0.3251 |
| 0.4914 | 3.2532 | 2300 | 0.4144 | 0.3236 |
| 0.4914 | 3.3946 | 2400 | 0.4140 | 0.3165 |
| 0.4011 | 3.5361 | 2500 | 0.4133 | 0.3157 |
| 0.4011 | 3.6775 | 2600 | 0.4086 | 0.3122 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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