---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: tiny-audio-embedded
  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. -->

# tiny-audio-embedded

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2044

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 2000
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.9934        | 0.0153 | 1000  | 0.3840          |
| 0.9974        | 0.0306 | 2000  | 0.4156          |
| 1.0350        | 0.0459 | 3000  | 0.3944          |
| 0.9922        | 0.0612 | 4000  | 0.3625          |
| 1.0129        | 0.0765 | 5000  | 0.3386          |
| 0.8650        | 0.0918 | 6000  | 0.3348          |
| 0.9696        | 0.1071 | 7000  | 0.3241          |
| 0.9879        | 0.1224 | 8000  | 0.3174          |
| 0.9225        | 0.1377 | 9000  | 0.3154          |
| 0.8560        | 0.1530 | 10000 | 0.3139          |
| 0.8554        | 0.1683 | 11000 | 0.3062          |
| 0.9126        | 0.1836 | 12000 | 0.3000          |
| 0.9142        | 0.1989 | 13000 | 0.2994          |
| 0.8358        | 0.2142 | 14000 | 0.2943          |
| 0.8452        | 0.2295 | 15000 | 0.2916          |
| 0.8372        | 0.2449 | 16000 | 0.2822          |
| 0.8776        | 0.2602 | 17000 | 0.2783          |
| 0.8697        | 0.2755 | 18000 | 0.2809          |
| 0.8541        | 0.2908 | 19000 | 0.2765          |
| 0.8511        | 0.3061 | 20000 | 0.2728          |
| 0.8440        | 0.3214 | 21000 | 0.2739          |
| 0.7897        | 0.3367 | 22000 | 0.2648          |
| 0.8196        | 0.3520 | 23000 | 0.2608          |
| 0.8320        | 0.3673 | 24000 | 0.2614          |
| 0.8043        | 0.3826 | 25000 | 0.2636          |
| 0.7875        | 0.3979 | 26000 | 0.2551          |
| 0.8257        | 0.4132 | 27000 | 0.2501          |
| 0.7276        | 0.4285 | 28000 | 0.2519          |
| 0.8196        | 0.4438 | 29000 | 0.2482          |
| 0.7727        | 0.4591 | 30000 | 0.2497          |
| 0.8316        | 0.4744 | 31000 | 0.2467          |
| 0.7738        | 0.4897 | 32000 | 0.2404          |
| 0.8146        | 0.5050 | 33000 | 0.2410          |
| 0.7571        | 0.5203 | 34000 | 0.2370          |
| 0.7921        | 0.5356 | 35000 | 0.2344          |
| 0.7792        | 0.5509 | 36000 | 0.2319          |
| 0.7014        | 0.5662 | 37000 | 0.2322          |
| 0.7425        | 0.5815 | 38000 | 0.2281          |
| 0.7644        | 0.5968 | 39000 | 0.2265          |
| 0.7048        | 0.6121 | 40000 | 0.2251          |
| 0.6970        | 0.6274 | 41000 | 0.2229          |
| 0.7856        | 0.6427 | 42000 | 0.2214          |
| 0.7114        | 0.6580 | 43000 | 0.2194          |
| 0.7751        | 0.6733 | 44000 | 0.2183          |
| 0.6482        | 0.6886 | 45000 | 0.2169          |
| 0.6889        | 0.7040 | 46000 | 0.2154          |
| 0.7554        | 0.7193 | 47000 | 0.2147          |
| 0.7050        | 0.7346 | 48000 | 0.2124          |
| 0.7927        | 0.7499 | 49000 | 0.2118          |
| 0.7309        | 0.7652 | 50000 | 0.2108          |
| 0.7264        | 0.7805 | 51000 | 0.2108          |
| 0.7256        | 0.7958 | 52000 | 0.2087          |
| 0.7605        | 0.8111 | 53000 | 0.2078          |
| 0.7391        | 0.8264 | 54000 | 0.2082          |
| 0.6781        | 0.8417 | 55000 | 0.2065          |
| 0.7206        | 0.8570 | 56000 | 0.2060          |
| 0.7342        | 0.8723 | 57000 | 0.2051          |
| 0.7519        | 0.8876 | 58000 | 0.2055          |
| 0.7258        | 0.9029 | 59000 | 0.2051          |
| 0.7932        | 0.9182 | 60000 | 0.2047          |
| 0.7391        | 0.9335 | 61000 | 0.2047          |
| 0.7416        | 0.9488 | 62000 | 0.2046          |
| 0.7249        | 0.9641 | 63000 | 0.2045          |
| 0.7000        | 0.9794 | 64000 | 0.2044          |
| 0.6958        | 0.9947 | 65000 | 0.2044          |
| 0.6692        | 1.0    | 65346 | 0.2044          |


### Framework versions

- Transformers 5.7.0
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2