metadata
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: W2V2-Bert_DigitalUmuganda_Afrivoice_Shona_10hr_v1
results: []
W2V2-Bert_DigitalUmuganda_Afrivoice_Shona_10hr_v1
This model is a fine-tuned version of facebook/w2v-bert-2.0 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3724
- Wer: 0.3126
- Cer: 0.0617
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
2.241 | 0.9977 | 220 | 0.3383 | 0.3722 | 0.0674 |
0.2577 | 2.0 | 441 | 0.3071 | 0.3285 | 0.0612 |
0.2209 | 2.9977 | 661 | 0.2699 | 0.3233 | 0.0565 |
0.1901 | 4.0 | 882 | 0.2798 | 0.3381 | 0.0570 |
0.1665 | 4.9977 | 1102 | 0.2710 | 0.2862 | 0.0513 |
0.1479 | 6.0 | 1323 | 0.2761 | 0.2970 | 0.0530 |
0.1323 | 6.9977 | 1543 | 0.2726 | 0.2888 | 0.0508 |
0.1172 | 8.0 | 1764 | 0.2843 | 0.2831 | 0.0505 |
0.1021 | 8.9977 | 1984 | 0.2944 | 0.2760 | 0.0497 |
0.0901 | 10.0 | 2205 | 0.3071 | 0.3010 | 0.0526 |
0.0794 | 10.9977 | 2425 | 0.3066 | 0.2766 | 0.0487 |
0.0673 | 12.0 | 2646 | 0.3258 | 0.2884 | 0.0511 |
0.0572 | 12.9977 | 2866 | 0.3349 | 0.2940 | 0.0517 |
0.0497 | 14.0 | 3087 | 0.3684 | 0.2954 | 0.0510 |
0.0428 | 14.9977 | 3307 | 0.3969 | 0.2792 | 0.0498 |
0.035 | 16.0 | 3528 | 0.4034 | 0.3074 | 0.0518 |
0.0317 | 16.9977 | 3748 | 0.4106 | 0.2874 | 0.0501 |
0.0284 | 18.0 | 3969 | 0.4286 | 0.2845 | 0.0516 |
0.0227 | 18.9977 | 4189 | 0.4147 | 0.2959 | 0.0497 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.2.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1