metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-300m-closest-to-faroese-full-15k-steps_v7
results: []
wav2vec2-xls-r-300m-closest-to-faroese-full-15k-steps_v7
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2472
- Wer: 95.4633
- Cer: 32.3403
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- 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: 500
- training_steps: 15000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
13.1629 | 0.3349 | 1000 | 0.6152 | 63.3285 | 18.8424 |
10.2766 | 0.6698 | 2000 | 0.4313 | 49.4623 | 13.6814 |
7.9374 | 1.0044 | 3000 | 0.3649 | 43.9210 | 11.8791 |
7.6787 | 1.3392 | 4000 | 0.3353 | 40.3217 | 10.5091 |
7.4414 | 1.6741 | 5000 | 0.3097 | 38.5529 | 10.0199 |
5.6641 | 2.0087 | 6000 | 0.2806 | 37.1760 | 9.5132 |
19.8102 | 2.3436 | 7000 | 1.0119 | 81.0784 | 25.2870 |
21.6448 | 2.6785 | 8000 | 1.1365 | 77.7051 | 26.4944 |
20.3363 | 3.0131 | 9000 | 1.0859 | 88.1525 | 32.7446 |
20.0312 | 3.3479 | 10000 | 1.0513 | 88.4973 | 30.9106 |
21.5903 | 3.6828 | 11000 | 1.0996 | 90.2825 | 32.8604 |
21.0909 | 4.0174 | 12000 | 1.0407 | 84.0173 | 26.3710 |
23.4511 | 4.3523 | 13000 | 1.2414 | 80.7754 | 24.7467 |
23.5201 | 4.6872 | 14000 | 1.2473 | 95.4625 | 32.3366 |
24.6061 | 5.0218 | 15000 | 1.2472 | 95.4633 | 32.3403 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0