File size: 1,629 Bytes
cddf873 30af809 f78f543 30af809 81bf6f5 f92b25c f78f543 f92b25c cddf873 f92b25c cddf873 f78f543 cddf873 f78f543 f92b25c f78f543 cddf873 f92b25c cddf873 f92b25c cddf873 f92b25c cddf873 f92b25c cddf873 f92b25c cddf873 f92b25c cddf873 f92b25c cddf873 f92b25c cddf873 f92b25c f78f543 f92b25c f78f543 f92b25c cddf873 f92b25c cddf873 f92b25c f78f543 cddf873 f92b25c cddf873 f92b25c |
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 |
---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: 240615-wav2vec2-ASR-Chinese
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. -->
# 240615-wav2vec2-ASR-Chinese
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2831
- Wer: 0.2399
## 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: 5
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 6.25 | 100 | 1.2831 | 0.2399 |
| No log | 12.5 | 200 | 1.2996 | 0.2657 |
| No log | 18.75 | 300 | 1.3705 | 0.3092 |
| No log | 25.0 | 400 | 1.3119 | 0.3269 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
|