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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: 0.4105
- Wer: 0.3136
## 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 | 3.2195 | 1.0 |
| No log | 0.2829 | 200 | 3.1180 | 1.0 |
| No log | 0.4243 | 300 | 1.7236 | 0.9364 |
| No log | 0.5658 | 400 | 1.1579 | 0.7628 |
| 3.0279 | 0.7072 | 500 | 0.9558 | 0.6721 |
| 3.0279 | 0.8487 | 600 | 0.8189 | 0.6424 |
| 3.0279 | 0.9901 | 700 | 0.6973 | 0.5164 |
| 3.0279 | 1.1315 | 800 | 0.6183 | 0.4752 |
| 3.0279 | 1.2730 | 900 | 0.5936 | 0.4703 |
| 0.7925 | 1.4144 | 1000 | 0.5498 | 0.4304 |
| 0.7925 | 1.5559 | 1100 | 0.5286 | 0.4148 |
| 0.7925 | 1.6973 | 1200 | 0.5130 | 0.3974 |
| 0.7925 | 1.8388 | 1300 | 0.4878 | 0.3864 |
| 0.7925 | 1.9802 | 1400 | 0.4740 | 0.3733 |
| 0.62 | 2.1216 | 1500 | 0.4578 | 0.3593 |
| 0.62 | 2.2631 | 1600 | 0.4535 | 0.3500 |
| 0.62 | 2.4045 | 1700 | 0.4485 | 0.3497 |
| 0.62 | 2.5460 | 1800 | 0.4373 | 0.3431 |
| 0.62 | 2.6874 | 1900 | 0.4362 | 0.3429 |
| 0.4879 | 2.8289 | 2000 | 0.4236 | 0.3327 |
| 0.4879 | 2.9703 | 2100 | 0.4172 | 0.3257 |
| 0.4879 | 3.1117 | 2200 | 0.4206 | 0.3217 |
| 0.4879 | 3.2532 | 2300 | 0.4166 | 0.3199 |
| 0.4879 | 3.3946 | 2400 | 0.4134 | 0.3173 |
| 0.4036 | 3.5361 | 2500 | 0.4110 | 0.3159 |
| 0.4036 | 3.6775 | 2600 | 0.4105 | 0.3136 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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