tiny-gpt2-br
This model is a fine-tuned version of distilbert/distilgpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.2128
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: 0.0007
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.8959 | 0.1 | 1000 | 4.8993 |
| 4.6543 | 0.2 | 2000 | 4.4073 |
| 4.329 | 0.31 | 3000 | 4.1635 |
| 4.1446 | 0.41 | 4000 | 4.0202 |
| 4.0133 | 0.51 | 5000 | 3.9119 |
| 3.9236 | 0.61 | 6000 | 3.8271 |
| 3.8622 | 0.72 | 7000 | 3.7583 |
| 3.7928 | 0.82 | 8000 | 3.7028 |
| 3.7379 | 0.92 | 9000 | 3.6607 |
| 3.672 | 1.02 | 10000 | 3.6198 |
| 3.5527 | 1.12 | 11000 | 3.5873 |
| 3.5428 | 1.23 | 12000 | 3.5617 |
| 3.514 | 1.33 | 13000 | 3.5328 |
| 3.4959 | 1.43 | 14000 | 3.4995 |
| 3.4762 | 1.53 | 15000 | 3.4816 |
| 3.4621 | 1.63 | 16000 | 3.4536 |
| 3.4392 | 1.74 | 17000 | 3.4368 |
| 3.4149 | 1.84 | 18000 | 3.4150 |
| 3.4006 | 1.94 | 19000 | 3.3950 |
| 3.3313 | 2.04 | 20000 | 3.3951 |
| 3.228 | 2.15 | 21000 | 3.3820 |
| 3.223 | 2.25 | 22000 | 3.3694 |
| 3.2234 | 2.35 | 23000 | 3.3470 |
| 3.215 | 2.45 | 24000 | 3.3350 |
| 3.2037 | 2.55 | 25000 | 3.3257 |
| 3.2265 | 2.66 | 26000 | 3.3122 |
| 3.2012 | 2.76 | 27000 | 3.2943 |
| 3.1827 | 2.86 | 28000 | 3.2816 |
| 3.1801 | 2.96 | 29000 | 3.2706 |
| 3.0519 | 3.06 | 30000 | 3.2998 |
| 3.0003 | 3.17 | 31000 | 3.2847 |
| 3.0091 | 3.27 | 32000 | 3.2764 |
| 3.0007 | 3.37 | 33000 | 3.2682 |
| 3.0013 | 3.47 | 34000 | 3.2586 |
| 2.9951 | 3.58 | 35000 | 3.2452 |
| 2.9943 | 3.68 | 36000 | 3.2452 |
| 2.9941 | 3.78 | 37000 | 3.2311 |
| 2.9839 | 3.88 | 38000 | 3.2174 |
| 2.9861 | 3.98 | 39000 | 3.2149 |
| 2.8311 | 4.09 | 40000 | 3.2509 |
| 2.8113 | 4.19 | 41000 | 3.2432 |
| 2.8074 | 4.29 | 42000 | 3.2450 |
| 2.8123 | 4.39 | 43000 | 3.2359 |
| 2.8086 | 4.5 | 44000 | 3.2245 |
| 2.8028 | 4.6 | 45000 | 3.2261 |
| 2.8046 | 4.7 | 46000 | 3.2204 |
| 2.7978 | 4.8 | 47000 | 3.2148 |
| 2.7982 | 4.9 | 48000 | 3.2128 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2