File size: 3,641 Bytes
21144a0 |
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 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-1b-ur
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: ur
split: test
args: ur
metrics:
- name: Wer
type: wer
value: 0.48854134406937133
---
<!-- 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-xls-r-1b-ur
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.4885
## 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: 6
- eval_batch_size: 6
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 12
- total_eval_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.7368 | 0.48 | 300 | inf | 0.8191 |
| 1.8995 | 0.97 | 600 | inf | 0.7919 |
| 0.9144 | 1.45 | 900 | inf | 0.7805 |
| 1.166 | 1.94 | 1200 | inf | 0.7087 |
| 0.7972 | 2.42 | 1500 | inf | 0.6901 |
| 0.8604 | 2.9 | 1800 | inf | 0.6446 |
| 0.6569 | 3.39 | 2100 | inf | 0.6560 |
| 0.7267 | 3.87 | 2400 | inf | 0.6363 |
| 0.687 | 4.35 | 2700 | inf | 0.6343 |
| 0.7143 | 4.84 | 3000 | inf | 0.6176 |
| 0.5283 | 5.32 | 3300 | inf | 0.6084 |
| 0.6917 | 5.81 | 3600 | inf | 0.5942 |
| 0.5396 | 6.29 | 3900 | inf | 0.5988 |
| 0.5523 | 6.77 | 4200 | inf | 0.5600 |
| 0.3167 | 7.26 | 4500 | inf | 0.5648 |
| 0.3176 | 7.74 | 4800 | inf | 0.5424 |
| 0.3987 | 8.23 | 5100 | inf | 0.5440 |
| 0.3327 | 8.71 | 5400 | inf | 0.5316 |
| 0.1936 | 9.19 | 5700 | inf | 0.5285 |
| 0.4701 | 9.68 | 6000 | inf | 0.5207 |
| 0.3581 | 10.16 | 6300 | inf | 0.5176 |
| 0.4038 | 10.65 | 6600 | inf | 0.5259 |
| 0.2699 | 11.13 | 6900 | inf | 0.5226 |
| 0.2302 | 11.61 | 7200 | inf | 0.5181 |
| 0.3275 | 12.1 | 7500 | inf | 0.5202 |
| 0.3024 | 12.58 | 7800 | inf | 0.5307 |
| 0.2568 | 13.06 | 8100 | inf | 0.5243 |
| 0.1641 | 13.55 | 8400 | inf | 0.5073 |
| 0.2637 | 14.03 | 8700 | inf | 0.5015 |
| 0.1778 | 14.52 | 9000 | inf | 0.4892 |
| 0.0874 | 15.0 | 9300 | inf | 0.4885 |
### Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1
- Tokenizers 0.13.2
|