---
library_name: transformers
license: apache-2.0
base_model: amd/AMD-Llama-135m
tags:
- generated_from_trainer
model-index:
- name: amdchess-v6
  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. -->

# amdchess-v6

This model is a fine-tuned version of [amd/AMD-Llama-135m](https://huggingface.co/amd/AMD-Llama-135m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7752

## 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.GROKADAMW with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 0.25

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 5.2893        | 0.0030 | 5    | 4.4359          |
| 1.9121        | 0.0059 | 10   | 1.6234          |
| 1.5379        | 0.0089 | 15   | 1.5644          |
| 1.4848        | 0.0118 | 20   | 1.4063          |
| 1.3139        | 0.0148 | 25   | 1.2141          |
| 1.3932        | 0.0177 | 30   | 1.1964          |
| 1.0851        | 0.0207 | 35   | 1.2140          |
| 1.4024        | 0.0236 | 40   | 1.1328          |
| 1.0103        | 0.0266 | 45   | 1.0825          |
| 1.0929        | 0.0295 | 50   | 1.0315          |
| 1.0656        | 0.0325 | 55   | 1.1649          |
| 1.2373        | 0.0354 | 60   | 1.0288          |
| 0.9401        | 0.0384 | 65   | 1.0114          |
| 1.0497        | 0.0413 | 70   | 1.0588          |
| 1.045         | 0.0443 | 75   | 0.9853          |
| 0.8332        | 0.0472 | 80   | 1.0362          |
| 0.9828        | 0.0502 | 85   | 0.9737          |
| 0.9275        | 0.0531 | 90   | 0.9487          |
| 0.98          | 0.0561 | 95   | 0.9751          |
| 0.9864        | 0.0590 | 100  | 0.9215          |
| 0.9425        | 0.0620 | 105  | 0.9404          |
| 0.965         | 0.0649 | 110  | 0.9259          |
| 0.9435        | 0.0679 | 115  | 0.9167          |
| 0.9628        | 0.0708 | 120  | 0.9259          |
| 0.9193        | 0.0738 | 125  | 0.8986          |
| 0.9385        | 0.0767 | 130  | 0.9031          |
| 0.8773        | 0.0797 | 135  | 0.8952          |
| 0.7856        | 0.0826 | 140  | 0.8779          |
| 0.9448        | 0.0856 | 145  | 0.8809          |
| 0.8727        | 0.0885 | 150  | 0.8683          |
| 0.9208        | 0.0915 | 155  | 0.8790          |
| 0.8647        | 0.0945 | 160  | 0.8663          |
| 0.8454        | 0.0974 | 165  | 0.8706          |
| 0.9631        | 0.1004 | 170  | 0.8615          |
| 0.8628        | 0.1033 | 175  | 0.8588          |
| 0.9279        | 0.1063 | 180  | 0.8537          |
| 0.862         | 0.1092 | 185  | 0.8468          |
| 0.9091        | 0.1122 | 190  | 0.8471          |
| 0.8762        | 0.1151 | 195  | 0.8434          |
| 0.8887        | 0.1181 | 200  | 0.8431          |
| 0.823         | 0.1210 | 205  | 0.8388          |
| 0.8025        | 0.1240 | 210  | 0.8356          |
| 0.8372        | 0.1269 | 215  | 0.8315          |
| 0.7744        | 0.1299 | 220  | 0.8251          |
| 0.8919        | 0.1328 | 225  | 0.8212          |
| 0.7742        | 0.1358 | 230  | 0.8206          |
| 0.8345        | 0.1387 | 235  | 0.8170          |
| 0.8442        | 0.1417 | 240  | 0.8162          |
| 0.8268        | 0.1446 | 245  | 0.8149          |
| 0.8138        | 0.1476 | 250  | 0.8102          |
| 0.8336        | 0.1505 | 255  | 0.8086          |
| 0.889         | 0.1535 | 260  | 0.8088          |
| 0.7523        | 0.1564 | 265  | 0.8057          |
| 0.7892        | 0.1594 | 270  | 0.8049          |
| 0.7574        | 0.1623 | 275  | 0.8002          |
| 0.8518        | 0.1653 | 280  | 0.7987          |
| 0.8566        | 0.1682 | 285  | 0.7990          |
| 0.7946        | 0.1712 | 290  | 0.7967          |
| 0.8028        | 0.1741 | 295  | 0.7942          |
| 0.8159        | 0.1771 | 300  | 0.7932          |
| 0.7905        | 0.1800 | 305  | 0.7901          |
| 0.8025        | 0.1830 | 310  | 0.7899          |
| 0.7278        | 0.1860 | 315  | 0.7889          |
| 0.8105        | 0.1889 | 320  | 0.7878          |
| 0.7161        | 0.1919 | 325  | 0.7869          |
| 0.7971        | 0.1948 | 330  | 0.7847          |
| 0.7943        | 0.1978 | 335  | 0.7841          |
| 0.7868        | 0.2007 | 340  | 0.7831          |
| 0.7387        | 0.2037 | 345  | 0.7814          |
| 0.8157        | 0.2066 | 350  | 0.7804          |
| 0.8196        | 0.2096 | 355  | 0.7797          |
| 0.8074        | 0.2125 | 360  | 0.7793          |
| 0.8144        | 0.2155 | 365  | 0.7783          |
| 0.7863        | 0.2184 | 370  | 0.7775          |
| 0.7865        | 0.2214 | 375  | 0.7769          |
| 0.8075        | 0.2243 | 380  | 0.7765          |
| 0.8684        | 0.2273 | 385  | 0.7762          |
| 0.7657        | 0.2302 | 390  | 0.7759          |
| 0.7928        | 0.2332 | 395  | 0.7757          |
| 0.8031        | 0.2361 | 400  | 0.7755          |
| 0.738         | 0.2391 | 405  | 0.7753          |
| 0.7716        | 0.2420 | 410  | 0.7752          |
| 0.7283        | 0.2450 | 415  | 0.7752          |
| 0.8095        | 0.2479 | 420  | 0.7752          |


### Framework versions

- Transformers 4.46.0
- Pytorch 2.4.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1