File size: 3,289 Bytes
40370e3 edfd598 40370e3 9b09bbe 40370e3 3528274 40370e3 d02b06f 74b237f 40370e3 9b09bbe 3528274 40370e3 74b237f 9b09bbe 3528274 40370e3 66985d8 40370e3 |
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 80 81 82 83 84 85 86 87 88 89 90 91 92 |
---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-ft-btb-ccv-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-ccv-cy
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Wer: 1.0
## 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: 8
- 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: 1500
- training_steps: 15000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 5.7778 | 0.0321 | 500 | 2.8852 | 1.0 |
| 1.4914 | 0.0641 | 1000 | 1.2012 | 0.7806 |
| 0.8803 | 0.0962 | 1500 | 1.1212 | 0.7590 |
| 0.7723 | 0.1283 | 2000 | 0.9681 | 0.6770 |
| 0.6988 | 0.1603 | 2500 | 0.9453 | 0.6599 |
| 0.6392 | 0.1924 | 3000 | 0.8691 | 0.6200 |
| 0.6114 | 0.2244 | 3500 | 0.8661 | 0.6192 |
| 0.5807 | 0.2565 | 4000 | 0.7885 | 0.5794 |
| 0.5534 | 0.2886 | 4500 | 0.7739 | 0.5490 |
| 0.5358 | 0.3206 | 5000 | 0.7416 | 0.5415 |
| 0.5189 | 0.3527 | 5500 | 0.7362 | 0.5303 |
| 0.4991 | 0.3848 | 6000 | 0.7188 | 0.5066 |
| 0.48 | 0.4168 | 6500 | 0.6985 | 0.5178 |
| 0.463 | 0.4489 | 7000 | 0.6682 | 0.4933 |
| 0.4477 | 0.4810 | 7500 | 0.6625 | 0.4867 |
| 0.4431 | 0.5130 | 8000 | 0.6374 | 0.4736 |
| 0.4392 | 0.5451 | 8500 | 0.6392 | 0.4772 |
| 0.4197 | 0.5771 | 9000 | 0.6159 | 0.4547 |
| 0.4147 | 0.6092 | 9500 | 0.5995 | 0.4522 |
| 0.3912 | 0.6413 | 10000 | 0.5848 | 0.4286 |
| 0.3742 | 0.6733 | 10500 | 0.5850 | 0.4259 |
| 0.402 | 0.7054 | 11000 | 0.6352 | 0.4489 |
| 0.5746 | 0.7375 | 11500 | 0.7712 | 0.5171 |
| 0.5783 | 0.7695 | 12000 | nan | 1.0 |
| 0.0 | 0.8016 | 12500 | nan | 1.0 |
| 0.0 | 0.8337 | 13000 | nan | 1.0 |
| 0.0 | 0.8657 | 13500 | nan | 1.0 |
| 0.0 | 0.8978 | 14000 | nan | 1.0 |
| 0.0 | 0.9298 | 14500 | nan | 1.0 |
| 0.0 | 0.9619 | 15000 | nan | 1.0 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
|