File size: 2,190 Bytes
27c3c92 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 |
---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2_bert_ru
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# w2v2_bert_ru
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.0538
## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.711 | 0.73 | 300 | inf | 0.1267 |
| 0.1026 | 1.46 | 600 | inf | 0.0925 |
| 0.0748 | 2.18 | 900 | inf | 0.0732 |
| 0.0591 | 2.91 | 1200 | inf | 0.0710 |
| 0.0437 | 3.64 | 1500 | inf | 0.0675 |
| 0.0382 | 4.37 | 1800 | inf | 0.0675 |
| 0.0302 | 5.1 | 2100 | inf | 0.0620 |
| 0.0243 | 5.83 | 2400 | inf | 0.0590 |
| 0.0219 | 6.55 | 2700 | inf | 0.0584 |
| 0.0173 | 7.28 | 3000 | inf | 0.0577 |
| 0.015 | 8.01 | 3300 | inf | 0.0560 |
| 0.0115 | 8.74 | 3600 | inf | 0.0551 |
| 0.0099 | 9.47 | 3900 | inf | 0.0538 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
|