metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- DewiBrynJones/banc-trawsgrifiadau-bangor-normalized-with-ccv
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-ft-btb-ccv-cy
results: []
wav2vec2-xlsr-53-ft-btb-ccv-cy
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the DEWIBRYNJONES/BANC-TRAWSGRIFIADAU-BANGOR-NORMALIZED-WITH-CCV - DEFAULT dataset. It achieves the following results on the evaluation set:
- Loss: 0.4198
- Wer: 0.3249
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 | 0.1046 | 100 | 3.5059 | 1.0 |
No log | 0.2092 | 200 | 3.2687 | 1.0 |
No log | 0.3138 | 300 | 2.7369 | 1.0 |
No log | 0.4184 | 400 | 1.3039 | 0.8545 |
3.5426 | 0.5230 | 500 | 1.0518 | 0.7738 |
3.5426 | 0.6276 | 600 | 0.8396 | 0.6149 |
3.5426 | 0.7322 | 700 | 0.7548 | 0.5687 |
3.5426 | 0.8368 | 800 | 0.6869 | 0.5185 |
3.5426 | 0.9414 | 900 | 0.6501 | 0.4895 |
0.7785 | 1.0460 | 1000 | 0.5817 | 0.4501 |
0.7785 | 1.1506 | 1100 | 0.5647 | 0.4288 |
0.7785 | 1.2552 | 1200 | 0.5424 | 0.4279 |
0.7785 | 1.3598 | 1300 | 0.5264 | 0.4051 |
0.7785 | 1.4644 | 1400 | 0.5099 | 0.3977 |
0.5795 | 1.5690 | 1500 | 0.5058 | 0.3953 |
0.5795 | 1.6736 | 1600 | 0.4804 | 0.3789 |
0.5795 | 1.7782 | 1700 | 0.4672 | 0.3698 |
0.5795 | 1.8828 | 1800 | 0.4605 | 0.3712 |
0.5795 | 1.9874 | 1900 | 0.4491 | 0.3556 |
0.5057 | 2.0921 | 2000 | 0.4494 | 0.3453 |
0.5057 | 2.1967 | 2100 | 0.4432 | 0.3397 |
0.5057 | 2.3013 | 2200 | 0.4378 | 0.3351 |
0.5057 | 2.4059 | 2300 | 0.4291 | 0.3310 |
0.5057 | 2.5105 | 2400 | 0.4279 | 0.3294 |
0.3986 | 2.6151 | 2500 | 0.4234 | 0.3259 |
0.3986 | 2.7197 | 2600 | 0.4198 | 0.3249 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1