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---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
- cer
model-index:
- name: JP-base-clean-0215
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: audiofolder
type: audiofolder
config: default
split: train
args: default
metrics:
- name: Wer
type: wer
value: 0.983
- name: Cer
type: cer
value: 0.012
---
<!-- 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. -->
# JP-base-clean-0215
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0988
- Cer: 0.012
## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 3125.0
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-----:|
| 5.5004 | 1.0 | 625 | 7.2647 | 1.0 |
| 4.0716 | 2.0 | 1250 | 4.3871 | 1.0 |
| 3.3302 | 3.0 | 1875 | 3.1038 | 1.0 |
| 0.8423 | 4.0 | 2500 | 0.9833 | 0.998 |
| 0.5152 | 5.0 | 3125 | 0.7318 | 0.996 |
| 0.3984 | 6.0 | 3750 | 0.4784 | 0.996 |
| 0.3481 | 7.0 | 4375 | 0.3688 | 0.994 |
| 0.3149 | 8.0 | 5000 | 0.3821 | 0.994 |
| 0.2852 | 9.0 | 5625 | 0.2320 | 0.992 |
| 0.2576 | 10.0 | 6250 | 0.2887 | 0.991 |
| 0.2423 | 11.0 | 6875 | 0.2071 | 0.991 |
| 0.2278 | 12.0 | 7500 | 0.1700 | 0.989 |
| 0.2104 | 13.0 | 8125 | 0.1553 | 0.991 |
| 0.2016 | 14.0 | 8750 | 0.1500 | 0.988 |
| 0.1967 | 15.0 | 9375 | 0.1357 | 0.985 |
| 0.1838 | 16.0 | 10000 | 0.1615 | 0.988 |
| 0.172 | 17.0 | 10625 | 0.1238 | 0.986 |
| 0.1687 | 18.0 | 11250 | 0.1270 | 0.988 |
| 0.1555 | 19.0 | 11875 | 0.1221 | 0.987 |
| 0.1532 | 20.0 | 12500 | 0.1168 | 0.988 |
| 0.1414 | 21.0 | 13125 | 0.1175 | 0.988 |
| 0.1366 | 22.0 | 13750 | 0.1231 | 0.985 |
| 0.1341 | 23.0 | 14375 | 0.1004 | 0.987 |
| 0.1273 | 24.0 | 15000 | 0.1175 | 0.984 |
| 0.1199 | 25.0 | 15625 | 0.1246 | 0.984 |
| 0.1181 | 26.0 | 16250 | 0.1382 | 0.985 |
| 0.1152 | 27.0 | 16875 | 0.1064 | 0.984 |
| 0.1116 | 28.0 | 17500 | 0.1075 | 0.985 |
| 0.1097 | 29.0 | 18125 | 0.1110 | 0.986 |
| 0.1074 | 30.0 | 18750 | 0.1399 | 0.983 |
| 0.0997 | 31.0 | 19375 | 0.1385 | 0.983 |
| 0.0998 | 32.0 | 20000 | 0.1185 | 0.983 |
| 0.0973 | 33.0 | 20625 | 0.1491 | 0.982 |
| 0.0988 | 34.0 | 21250 | 0.1232 | 0.983 |
| 0.0942 | 35.0 | 21875 | 0.1205 | 0.98 |
| 0.0949 | 36.0 | 22500 | 0.1109 | 0.981 |
| 0.0947 | 37.0 | 23125 | 0.1119 | 0.982 |
| 0.0939 | 38.0 | 23750 | 0.1151 | 0.983 |
| 0.0876 | 39.0 | 24375 | 0.1001 | 0.982 |
| 0.0893 | 40.0 | 25000 | 0.0957 | 0.984 |
| 0.0897 | 41.0 | 25625 | 0.0924 | 0.982 |
| 0.0859 | 42.0 | 26250 | 0.0959 | 0.983 |
| 0.0881 | 43.0 | 26875 | 0.0996 | 0.983 |
| 0.0885 | 44.0 | 27500 | 0.0972 | 0.982 |
| 0.0871 | 45.0 | 28125 | 0.0984 | 0.983 |
| 0.0866 | 46.0 | 28750 | 0.0976 | 0.983 |
| 0.0858 | 47.0 | 29375 | 0.0982 | 0.983 |
| 0.0882 | 48.0 | 30000 | 0.0982 | 0.983 |
| 0.0848 | 49.0 | 30625 | 0.0988 | 0.983 |
| 0.0855 | 50.0 | 31250 | 0.0988 | 0.983 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.1 |