File size: 2,656 Bytes
9acbcb3 261e12d 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 9acbcb3 4db1380 |
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 78 79 80 81 82 |
---
base_model: facebook/wav2vec2-xls-r-1b
library_name: transformers
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-1b-E10_freq_speed
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. -->
# wav2vec2-1b-E10_freq_speed
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7340
- Cer: 19.0026
## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 11.3207 | 0.2580 | 200 | 3.4053 | 86.8891 |
| 1.8939 | 0.5160 | 400 | 1.8047 | 41.0303 |
| 1.1854 | 0.7741 | 600 | 1.4651 | 34.3691 |
| 0.9917 | 1.0321 | 800 | 1.0588 | 25.9516 |
| 0.744 | 1.2901 | 1000 | 1.1790 | 27.6962 |
| 0.6919 | 1.5481 | 1200 | 1.0604 | 25.9927 |
| 0.6347 | 1.8062 | 1400 | 0.9300 | 22.9323 |
| 0.5428 | 2.0642 | 1600 | 0.9996 | 24.9648 |
| 0.4724 | 2.3222 | 1800 | 0.9695 | 23.8252 |
| 0.4267 | 2.5802 | 2000 | 0.9463 | 23.7606 |
| 0.4096 | 2.8383 | 2200 | 0.8589 | 22.4448 |
| 0.3507 | 3.0963 | 2400 | 0.8145 | 20.7707 |
| 0.2874 | 3.3543 | 2600 | 0.8739 | 22.6856 |
| 0.2767 | 3.6123 | 2800 | 0.8657 | 21.8280 |
| 0.2663 | 3.8703 | 3000 | 0.8732 | 22.0630 |
| 0.2196 | 4.1284 | 3200 | 0.7671 | 19.4843 |
| 0.1867 | 4.3864 | 3400 | 0.7652 | 19.7016 |
| 0.1685 | 4.6444 | 3600 | 0.7288 | 18.7559 |
| 0.1677 | 4.9024 | 3800 | 0.7340 | 19.0026 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.3.1.post100
- Datasets 2.19.1
- Tokenizers 0.20.1
|