transcribe-monkey / README.md
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---
library_name: transformers
license: apache-2.0
base_model: superb/wav2vec2-base-superb-sid
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: transcribe-monkey
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. -->
# transcribe-monkey
This model is a fine-tuned version of [superb/wav2vec2-base-superb-sid](https://huggingface.co/superb/wav2vec2-base-superb-sid) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2787
- Accuracy: 0.9677
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1226 | 1.0 | 212 | 0.4222 | 0.9516 |
| 0.2144 | 2.0 | 424 | 0.2416 | 0.9516 |
| 0.0888 | 3.0 | 636 | 0.2240 | 0.9677 |
| 0.0004 | 4.0 | 848 | 0.3074 | 0.9677 |
| 0.0204 | 5.0 | 1060 | 0.2787 | 0.9677 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.3.0
- Datasets 3.1.0
- Tokenizers 0.20.3