metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-1b-irish-5h-11k-steps
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: ga-IE
split: test
args: ga-IE
metrics:
- name: Wer
type: wer
value: 99.97108991037872
wav2vec2-xls-r-1b-irish-5h-11k-steps
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Wer: 99.9711
- Cer: 99.9943
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 3000
- training_steps: 11000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 2.9708 | 6.25 | 1000 | 2.8622 | 94.9986 | 93.1290 |
| 4.3506 | 12.5 | 2000 | 4.2474 | 96.5019 | 92.1035 |
| 4.4125 | 18.75 | 3000 | 4.2473 | 96.5019 | 92.2060 |
| 4.4092 | 25.0 | 4000 | 4.2474 | 96.3862 | 91.9781 |
| 4.436 | 31.25 | 5000 | 4.2474 | 96.4151 | 92.0978 |
| 4.4694 | 37.5 | 6000 | 4.2473 | 96.4441 | 92.1206 |
| 4.3806 | 43.75 | 7000 | 4.2474 | 96.3862 | 92.1775 |
| 4.4963 | 50.0 | 8000 | 4.2473 | 96.3862 | 92.0579 |
| 0.0 | 56.25 | 9000 | nan | 99.9711 | 99.9943 |
| 0.0 | 62.5 | 10000 | nan | 99.9711 | 99.9943 |
| 0.0 | 68.75 | 11000 | nan | 99.9711 | 99.9943 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3