metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-E30_speed2
results: []
wav2vec2-E30_speed2
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2995
- Cer: 25.2938
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: 8
- eval_batch_size: 8
- seed: 42
- 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: 50
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Cer |
---|---|---|---|---|
41.4516 | 0.1289 | 200 | 5.3911 | 100.0 |
4.9936 | 0.2579 | 400 | 4.7064 | 100.0 |
4.8068 | 0.3868 | 600 | 4.6491 | 100.0 |
4.7989 | 0.5158 | 800 | 4.7160 | 100.0 |
4.7287 | 0.6447 | 1000 | 4.5872 | 100.0 |
4.7102 | 0.7737 | 1200 | 4.5938 | 100.0 |
4.6927 | 0.9026 | 1400 | 4.6049 | 100.0 |
4.6106 | 1.0316 | 1600 | 4.5710 | 100.0 |
4.5281 | 1.1605 | 1800 | 4.4045 | 100.0 |
4.2276 | 1.2895 | 2000 | 3.8233 | 74.6240 |
3.2563 | 1.4184 | 2200 | 2.8222 | 51.8508 |
2.5657 | 1.5474 | 2400 | 2.3714 | 42.7850 |
2.2757 | 1.6763 | 2600 | 2.1794 | 41.1163 |
2.0428 | 1.8053 | 2800 | 1.9496 | 36.1222 |
1.8705 | 1.9342 | 3000 | 1.8052 | 33.6310 |
1.6822 | 2.0632 | 3200 | 1.6552 | 31.3514 |
1.574 | 2.1921 | 3400 | 1.5774 | 30.2115 |
1.4683 | 2.3211 | 3600 | 1.4999 | 28.9424 |
1.4039 | 2.4500 | 3800 | 1.4358 | 28.1786 |
1.3323 | 2.5790 | 4000 | 1.3441 | 26.1868 |
1.3055 | 2.7079 | 4200 | 1.3460 | 25.8813 |
1.2428 | 2.8369 | 4400 | 1.3022 | 25.5170 |
1.2121 | 2.9658 | 4600 | 1.2995 | 25.2938 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3