File size: 2,508 Bytes
659b86f 9a3f429 659b86f 9a3f429 659b86f f5d11fc 659b86f ac86de4 659b86f ac86de4 659b86f f5d11fc 659b86f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 |
---
license: apache-2.0
base_model: DewiBrynJones/wav2vec2-xlsr-53-ft-btb-ccv-cy
tags:
- automatic-speech-recognition
- DewiBrynJones/banc-trawsgrifiadau-bangor-clean
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-btb-ccv-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-btb-ccv-ft-btb-cy
This model is a fine-tuned version of [DewiBrynJones/wav2vec2-xlsr-53-ft-btb-ccv-cy](https://huggingface.co/DewiBrynJones/wav2vec2-xlsr-53-ft-btb-ccv-cy) on the DEWIBRYNJONES/BANC-TRAWSGRIFIADAU-BANGOR-CLEAN - DEFAULT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4314
- Wer: 0.3285
## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- training_steps: 3000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log | 0.1139 | 200 | 0.7148 | 0.4603 |
| No log | 0.2278 | 400 | 0.6810 | 0.4795 |
| 1.4735 | 0.3417 | 600 | 0.6035 | 0.4486 |
| 1.4735 | 0.4556 | 800 | 0.6223 | 0.5105 |
| 0.7681 | 0.5695 | 1000 | 0.5656 | 0.4336 |
| 0.7681 | 0.6834 | 1200 | 0.5275 | 0.4008 |
| 0.7681 | 0.7973 | 1400 | 0.5284 | 0.4028 |
| 0.7159 | 0.9112 | 1600 | 0.4990 | 0.3914 |
| 0.7159 | 1.0251 | 1800 | 0.4855 | 0.3730 |
| 0.6203 | 1.1390 | 2000 | 0.4740 | 0.3623 |
| 0.6203 | 1.2528 | 2200 | 0.4589 | 0.3536 |
| 0.6203 | 1.3667 | 2400 | 0.4539 | 0.3407 |
| 0.5447 | 1.4806 | 2600 | 0.4410 | 0.3357 |
| 0.5447 | 1.5945 | 2800 | 0.4347 | 0.3293 |
| 0.5392 | 1.7084 | 3000 | 0.4314 | 0.3285 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
|