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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: 0.4159
- Wer: 0.3171
## 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 | 3.4000 | 1.0 |
| No log | 0.2829 | 200 | 2.9513 | 1.0 |
| No log | 0.4243 | 300 | 1.9454 | 0.9325 |
| No log | 0.5658 | 400 | 1.1412 | 0.7730 |
| 3.2243 | 0.7072 | 500 | 0.9250 | 0.6789 |
| 3.2243 | 0.8487 | 600 | 0.8018 | 0.5983 |
| 3.2243 | 0.9901 | 700 | 0.7182 | 0.5409 |
| 3.2243 | 1.1315 | 800 | 0.6198 | 0.4770 |
| 3.2243 | 1.2730 | 900 | 0.6102 | 0.4712 |
| 0.7983 | 1.4144 | 1000 | 0.5605 | 0.4426 |
| 0.7983 | 1.5559 | 1100 | 0.5336 | 0.4162 |
| 0.7983 | 1.6973 | 1200 | 0.5259 | 0.4116 |
| 0.7983 | 1.8388 | 1300 | 0.4960 | 0.3872 |
| 0.7983 | 1.9802 | 1400 | 0.4857 | 0.3868 |
| 0.6274 | 2.1216 | 1500 | 0.4689 | 0.3656 |
| 0.6274 | 2.2631 | 1600 | 0.4680 | 0.3562 |
| 0.6274 | 2.4045 | 1700 | 0.4536 | 0.3535 |
| 0.6274 | 2.5460 | 1800 | 0.4486 | 0.3501 |
| 0.6274 | 2.6874 | 1900 | 0.4396 | 0.3505 |
| 0.4939 | 2.8289 | 2000 | 0.4299 | 0.3340 |
| 0.4939 | 2.9703 | 2100 | 0.4292 | 0.3311 |
| 0.4939 | 3.1117 | 2200 | 0.4276 | 0.3271 |
| 0.4939 | 3.2532 | 2300 | 0.4233 | 0.3260 |
| 0.4939 | 3.3946 | 2400 | 0.4192 | 0.3223 |
| 0.4072 | 3.5361 | 2500 | 0.4179 | 0.3195 |
| 0.4072 | 3.6775 | 2600 | 0.4159 | 0.3171 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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