---
tags:
- generated_from_trainer
model-index:
- name: model
  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. -->

# model

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: 0.1795

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.639         | 1.0   | 125   | 0.3439          |
| 0.365         | 2.0   | 250   | 0.2767          |
| 0.3371        | 3.0   | 375   | 0.2818          |
| 0.3215        | 4.0   | 500   | 0.2573          |
| 0.2982        | 5.0   | 625   | 0.2449          |
| 0.2912        | 6.0   | 750   | 0.2377          |
| 0.2886        | 7.0   | 875   | 0.2535          |
| 0.2853        | 8.0   | 1000  | 0.2426          |
| 0.2814        | 9.0   | 1125  | 0.2532          |
| 0.272         | 10.0  | 1250  | 0.2322          |
| 0.2774        | 11.0  | 1375  | 0.2395          |
| 0.2692        | 12.0  | 1500  | 0.2360          |
| 0.2633        | 13.0  | 1625  | 0.2373          |
| 0.256         | 14.0  | 1750  | 0.2400          |
| 0.2512        | 15.0  | 1875  | 0.2082          |
| 0.2502        | 16.0  | 2000  | 0.2222          |
| 0.2573        | 17.0  | 2125  | 0.2183          |
| 0.2493        | 18.0  | 2250  | 0.2073          |
| 0.2562        | 19.0  | 2375  | 0.2220          |
| 0.2462        | 20.0  | 2500  | 0.2305          |
| 0.2495        | 21.0  | 2625  | 0.2098          |
| 0.2486        | 22.0  | 2750  | 0.2149          |
| 0.2493        | 23.0  | 2875  | 0.2193          |
| 0.237         | 24.0  | 3000  | 0.2148          |
| 0.2421        | 25.0  | 3125  | 0.2141          |
| 0.2391        | 26.0  | 3250  | 0.2252          |
| 0.2463        | 27.0  | 3375  | 0.2304          |
| 0.238         | 28.0  | 3500  | 0.2062          |
| 0.2346        | 29.0  | 3625  | 0.2111          |
| 0.235         | 30.0  | 3750  | 0.2055          |
| 0.2316        | 31.0  | 3875  | 0.2091          |
| 0.2385        | 32.0  | 4000  | 0.2135          |
| 0.2296        | 33.0  | 4125  | 0.2124          |
| 0.225         | 34.0  | 4250  | 0.2078          |
| 0.2343        | 35.0  | 4375  | 0.2069          |
| 0.2252        | 36.0  | 4500  | 0.2068          |
| 0.2279        | 37.0  | 4625  | 0.2187          |
| 0.223         | 38.0  | 4750  | 0.1986          |
| 0.2255        | 39.0  | 4875  | 0.1970          |
| 0.2261        | 40.0  | 5000  | 0.1994          |
| 0.2203        | 41.0  | 5125  | 0.2056          |
| 0.2223        | 42.0  | 5250  | 0.1934          |
| 0.2259        | 43.0  | 5375  | 0.2028          |
| 0.2103        | 44.0  | 5500  | 0.2020          |
| 0.2199        | 45.0  | 5625  | 0.1959          |
| 0.2211        | 46.0  | 5750  | 0.2017          |
| 0.2235        | 47.0  | 5875  | 0.1948          |
| 0.2145        | 48.0  | 6000  | 0.2015          |
| 0.2116        | 49.0  | 6125  | 0.2114          |
| 0.216         | 50.0  | 6250  | 0.1966          |
| 0.216         | 51.0  | 6375  | 0.2107          |
| 0.2121        | 52.0  | 6500  | 0.1939          |
| 0.2099        | 53.0  | 6625  | 0.2167          |
| 0.2069        | 54.0  | 6750  | 0.1909          |
| 0.2129        | 55.0  | 6875  | 0.2070          |
| 0.2105        | 56.0  | 7000  | 0.1927          |
| 0.2092        | 57.0  | 7125  | 0.1957          |
| 0.2043        | 58.0  | 7250  | 0.2064          |
| 0.2072        | 59.0  | 7375  | 0.1915          |
| 0.2069        | 60.0  | 7500  | 0.1972          |
| 0.2009        | 61.0  | 7625  | 0.1977          |
| 0.2001        | 62.0  | 7750  | 0.1853          |
| 0.2058        | 63.0  | 7875  | 0.1976          |
| 0.1944        | 64.0  | 8000  | 0.1887          |
| 0.1985        | 65.0  | 8125  | 0.1932          |
| 0.2061        | 66.0  | 8250  | 0.1924          |
| 0.2028        | 67.0  | 8375  | 0.1888          |
| 0.2016        | 68.0  | 8500  | 0.1967          |
| 0.2           | 69.0  | 8625  | 0.1983          |
| 0.201         | 70.0  | 8750  | 0.1862          |
| 0.1975        | 71.0  | 8875  | 0.1943          |
| 0.2035        | 72.0  | 9000  | 0.1856          |
| 0.2008        | 73.0  | 9125  | 0.1957          |
| 0.1966        | 74.0  | 9250  | 0.1843          |
| 0.1945        | 75.0  | 9375  | 0.1864          |
| 0.1989        | 76.0  | 9500  | 0.1876          |
| 0.195         | 77.0  | 9625  | 0.1867          |
| 0.1984        | 78.0  | 9750  | 0.2041          |
| 0.1974        | 79.0  | 9875  | 0.1996          |
| 0.1918        | 80.0  | 10000 | 0.1694          |
| 0.1959        | 81.0  | 10125 | 0.1780          |
| 0.1965        | 82.0  | 10250 | 0.1738          |
| 0.1917        | 83.0  | 10375 | 0.2058          |
| 0.1911        | 84.0  | 10500 | 0.1806          |
| 0.1905        | 85.0  | 10625 | 0.1852          |
| 0.1934        | 86.0  | 10750 | 0.1765          |
| 0.1874        | 87.0  | 10875 | 0.1858          |
| 0.1921        | 88.0  | 11000 | 0.1790          |
| 0.1883        | 89.0  | 11125 | 0.1933          |
| 0.1854        | 90.0  | 11250 | 0.1785          |
| 0.189         | 91.0  | 11375 | 0.1849          |
| 0.1873        | 92.0  | 11500 | 0.1880          |
| 0.1866        | 93.0  | 11625 | 0.1758          |
| 0.1909        | 94.0  | 11750 | 0.1783          |
| 0.1821        | 95.0  | 11875 | 0.1936          |
| 0.1868        | 96.0  | 12000 | 0.1954          |
| 0.1846        | 97.0  | 12125 | 0.1793          |
| 0.1847        | 98.0  | 12250 | 0.1866          |
| 0.1877        | 99.0  | 12375 | 0.1677          |
| 0.1845        | 100.0 | 12500 | 0.1718          |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3