---
library_name: transformers
base_model: t-tech/T-lite-it-1.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: T-lite-it-1.0-pseudo-base
  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. -->

# t-lite_part1-2_lr1e4_wsd_bs128

This model is a fine-tuned version of [t-tech/T-lite-it-1.0](https://huggingface.co/t-tech/T-lite-it-1.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3980
- Accuracy: 0.6669

## 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
- seed: 42
- distributed_type: multi-GPU
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
- lr_scheduler_type: warmup_stable_decay
- lr_scheduler_warmup_steps: 100
- num_epochs: 0.5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log        | 0.0001 | 1    | 1.4751          | 0.6606   |
| 1.5071        | 0.0354 | 500  | 1.4113          | 0.6647   |
| 1.5003        | 0.0709 | 1000 | 1.4080          | 0.6649   |
| 1.4959        | 0.1063 | 1500 | 1.4063          | 0.6654   |
| 1.5019        | 0.1418 | 2000 | 1.4054          | 0.6655   |
| 1.4891        | 0.1772 | 2500 | 1.4047          | 0.6656   |
| 1.4916        | 0.2126 | 3000 | 1.4040          | 0.6657   |
| 1.496         | 0.2481 | 3500 | 1.4034          | 0.6657   |
| 1.495         | 0.2835 | 4000 | 1.4032          | 0.6657   |
| 1.4934        | 0.3189 | 4500 | 1.4030          | 0.6658   |
| 1.4849        | 0.3544 | 5000 | 1.4029          | 0.6660   |
| 1.4833        | 0.3898 | 5500 | 1.4024          | 0.6661   |
| 1.4909        | 0.4253 | 6000 | 1.4023          | 0.6661   |
| 1.4923        | 0.4607 | 6500 | 1.4000          | 0.6665   |
| 1.4965        | 0.4961 | 7000 | 1.3979          | 0.6669   |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.3.0a0+6ddf5cf85e.nv24.04
- Datasets 2.18.0
- Tokenizers 0.20.3