File size: 3,051 Bytes
bed1127 | 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 83 84 85 86 87 | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xlsr-53_train_data_full
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-large-xlsr-53_train_data_full
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4168
- Wer: 0.3383
## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.0459 | 0.73 | 500 | 3.2037 | 0.9995 |
| 0.7938 | 1.45 | 1000 | 0.7432 | 0.6373 |
| 0.503 | 2.18 | 1500 | 0.5517 | 0.5115 |
| 0.4475 | 2.91 | 2000 | 0.4916 | 0.4624 |
| 0.3575 | 3.63 | 2500 | 0.4612 | 0.4362 |
| 0.3206 | 4.36 | 3000 | 0.4546 | 0.4198 |
| 0.3155 | 5.09 | 3500 | 0.4073 | 0.3929 |
| 0.2827 | 5.81 | 4000 | 0.4172 | 0.3808 |
| 0.2575 | 6.54 | 4500 | 0.4183 | 0.3741 |
| 0.2399 | 7.27 | 5000 | 0.4181 | 0.3680 |
| 0.2455 | 7.99 | 5500 | 0.3981 | 0.3604 |
| 0.2512 | 8.72 | 6000 | 0.4203 | 0.3612 |
| 0.221 | 9.45 | 6500 | 0.4073 | 0.3560 |
| 0.19 | 10.17 | 7000 | 0.4206 | 0.3547 |
| 0.207 | 10.9 | 7500 | 0.3992 | 0.3517 |
| 0.187 | 11.63 | 8000 | 0.4078 | 0.3517 |
| 0.2029 | 12.35 | 8500 | 0.4143 | 0.3469 |
| 0.171 | 13.08 | 9000 | 0.4007 | 0.3430 |
| 0.1658 | 13.81 | 9500 | 0.3862 | 0.3422 |
| 0.2021 | 14.53 | 10000 | 0.4132 | 0.3454 |
| 0.165 | 15.26 | 10500 | 0.3997 | 0.3407 |
| 0.1562 | 15.99 | 11000 | 0.4069 | 0.3416 |
| 0.1613 | 16.71 | 11500 | 0.4040 | 0.3393 |
| 0.1713 | 17.44 | 12000 | 0.4094 | 0.3411 |
| 0.1541 | 18.17 | 12500 | 0.4043 | 0.3367 |
| 0.144 | 18.89 | 13000 | 0.4086 | 0.3374 |
| 0.1483 | 19.62 | 13500 | 0.4168 | 0.3383 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu102
- Datasets 2.1.0
- Tokenizers 0.12.1
|