T10
This model is a fine-tuned version of hhhhzy/deltalm-base-xlsum on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6357
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
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 64
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.805 | 1.0 | 6 | 0.3684 |
| 0.2843 | 2.0 | 12 | 0.3604 |
| 0.2494 | 3.0 | 18 | 0.3970 |
| 0.1528 | 4.0 | 24 | 0.4507 |
| 0.0779 | 5.0 | 30 | 0.5024 |
| 0.0482 | 6.0 | 36 | 0.5399 |
| 0.0246 | 7.0 | 42 | 0.5612 |
| 0.0202 | 8.0 | 48 | 0.5788 |
| 0.0172 | 9.0 | 54 | 0.6024 |
| 0.0147 | 10.0 | 60 | 0.6003 |
| 0.0115 | 11.0 | 66 | 0.5960 |
| 0.0124 | 12.0 | 72 | 0.6035 |
| 0.0122 | 13.0 | 78 | 0.6135 |
| 0.0121 | 14.0 | 84 | 0.6105 |
| 0.0101 | 15.0 | 90 | 0.6155 |
| 0.0103 | 16.0 | 96 | 0.6188 |
| 0.0087 | 17.0 | 102 | 0.6192 |
| 0.015 | 18.0 | 108 | 0.6113 |
| 0.0092 | 19.0 | 114 | 0.6141 |
| 0.0091 | 20.0 | 120 | 0.6220 |
| 0.0088 | 21.0 | 126 | 0.6243 |
| 0.009 | 22.0 | 132 | 0.6239 |
| 0.0085 | 23.0 | 138 | 0.6199 |
| 0.0093 | 24.0 | 144 | 0.6183 |
| 0.0092 | 25.0 | 150 | 0.6170 |
| 0.0086 | 26.0 | 156 | 0.6154 |
| 0.0084 | 27.0 | 162 | 0.6154 |
| 0.0082 | 28.0 | 168 | 0.6182 |
| 0.0083 | 29.0 | 174 | 0.6224 |
| 0.0082 | 30.0 | 180 | 0.6250 |
| 0.0086 | 31.0 | 186 | 0.6263 |
| 0.0078 | 32.0 | 192 | 0.6270 |
| 0.0081 | 33.0 | 198 | 0.6271 |
| 0.0081 | 34.0 | 204 | 0.6276 |
| 0.0082 | 35.0 | 210 | 0.6280 |
| 0.0078 | 36.0 | 216 | 0.6292 |
| 0.0078 | 37.0 | 222 | 0.6302 |
| 0.0079 | 38.0 | 228 | 0.6314 |
| 0.0081 | 39.0 | 234 | 0.6319 |
| 0.0083 | 40.0 | 240 | 0.6318 |
| 0.0076 | 41.0 | 246 | 0.6317 |
| 0.0079 | 42.0 | 252 | 0.6309 |
| 0.0084 | 43.0 | 258 | 0.6304 |
| 0.0078 | 44.0 | 264 | 0.6307 |
| 0.0079 | 45.0 | 270 | 0.6309 |
| 0.0076 | 46.0 | 276 | 0.6312 |
| 0.0076 | 47.0 | 282 | 0.6313 |
| 0.008 | 48.0 | 288 | 0.6316 |
| 0.0081 | 49.0 | 294 | 0.6320 |
| 0.0077 | 50.0 | 300 | 0.6323 |
| 0.0075 | 51.0 | 306 | 0.6328 |
| 0.0077 | 52.0 | 312 | 0.6336 |
| 0.0076 | 53.0 | 318 | 0.6342 |
| 0.0077 | 54.0 | 324 | 0.6344 |
| 0.0075 | 55.0 | 330 | 0.6346 |
| 0.0079 | 56.0 | 336 | 0.6350 |
| 0.0076 | 57.0 | 342 | 0.6350 |
| 0.0078 | 58.0 | 348 | 0.6355 |
| 0.0077 | 59.0 | 354 | 0.6357 |
| 0.0074 | 60.0 | 360 | 0.6358 |
| 0.0075 | 61.0 | 366 | 0.6358 |
| 0.0075 | 62.0 | 372 | 0.6358 |
| 0.0077 | 63.0 | 378 | 0.6357 |
| 0.0073 | 64.0 | 384 | 0.6357 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
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