metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-saha-yakut
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: sah
split: test
args: sah
metrics:
- name: Wer
type: wer
value: 0.5216510903426791
wav2vec2-large-xls-r-300m-saha-yakut
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6404
- Wer: 0.5217
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: 0.0002
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 3.4483 | 150 | 3.1675 | 1.0 |
| No log | 6.8966 | 300 | 1.1392 | 0.8509 |
| 3.5746 | 10.3448 | 450 | 0.6103 | 0.5812 |
| 3.5746 | 13.7931 | 600 | 0.6152 | 0.5565 |
| 3.5746 | 17.2414 | 750 | 0.6420 | 0.5382 |
| 0.2138 | 20.6897 | 900 | 0.6344 | 0.5245 |
| 0.2138 | 24.1379 | 1050 | 0.6543 | 0.5303 |
| 0.1148 | 27.5862 | 1200 | 0.6404 | 0.5217 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1