File size: 3,775 Bytes
3334104 319c507 3334104 319c507 3334104 319c507 3334104 319c507 a43a953 319c507 a43a953 319c507 3334104 a43a953 3334104 a43a953 3334104 |
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 |
---
language:
- ga-IE
license: apache-2.0
tags:
- automatic-speech-recognition
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
- cer
model-index:
- name: wav2vec2-large-xls-r-1b-Irish-Abid
results:
- task:
type: automatic-speech-recognition # Required. Example: automatic-speech-recognition
name: Speech Recognition # Optional. Example: Speech Recognition
dataset:
type: mozilla-foundation/common_voice_8_0 # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
name: Common Voice ga-IE # Required. Example: Common Voice zh-CN
args: ga-IE # Optional. Example: zh-CN
metrics:
- type: wer # Required. Example: wer
value: 38.45 # Required. Example: 20.90
name: Test WER With LM # Optional. Example: Test WER
- type: cer # Required. Example: wer
value: 16.52 # Required. Example: 20.90
name: Test CER With LM # Optional. Example: Test WER
---
<!-- 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-large-xls-r-1b-Irish
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 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3599
- Wer: 0.4236
- Cer: 0.1768
#### Evaluation Commands
1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test`
```bash
python eval.py --model_id kingabzpro/wav2vec2-large-xls-r-1b-Irish --dataset mozilla-foundation/common_voice_8_0 --config ga-IE --split test
```
### Inference With LM
```python
import torch
from datasets import load_dataset
from transformers import AutoModelForCTC, AutoProcessor
import torchaudio.functional as F
model_id = "kingabzpro/wav2vec2-large-xls-r-1b-Irish"
sample_iter = iter(load_dataset("mozilla-foundation/common_voice_8_0", "ga-IE", split="test", streaming=True, use_auth_token=True))
sample = next(sample_iter)
resampled_audio = F.resample(torch.tensor(sample["audio"]["array"]), 48_000, 16_000).numpy()
model = AutoModelForCTC.from_pretrained(model_id)
processor = AutoProcessor.from_pretrained(model_id)
input_values = processor(resampled_audio, return_tensors="pt").input_values
with torch.no_grad():
logits = model(input_values).logits
transcription = processor.batch_decode(logits.numpy()).text
```
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 7.5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 6.3955 | 12.48 | 100 | 2.9897 | 1.0 | 1.0 |
| 2.3811 | 24.97 | 200 | 1.2304 | 0.7140 | 0.3106 |
| 1.0476 | 37.48 | 300 | 1.0661 | 0.5597 | 0.2407 |
| 0.7014 | 49.97 | 400 | 1.1788 | 0.4799 | 0.1947 |
| 0.4409 | 62.48 | 500 | 1.2649 | 0.4658 | 0.1997 |
| 0.4839 | 74.97 | 600 | 1.3259 | 0.4450 | 0.1868 |
| 0.3643 | 87.48 | 700 | 1.3506 | 0.4312 | 0.1760 |
| 0.3468 | 99.97 | 800 | 1.3599 | 0.4236 | 0.1768 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0
|