File size: 2,469 Bytes
9cf7546 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 |
---
license: apache-2.0
base_model: distilbert/distilgpt2
tags:
- generated_from_trainer
model-index:
- name: tiny-gpt2-br
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. -->
# tiny-gpt2-br
This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co./distilbert/distilgpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6959
## 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: 0.0004
- train_batch_size: 16
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 5.966 | 0.21 | 1000 | 5.0526 |
| 4.8376 | 0.42 | 2000 | 4.6063 |
| 4.5265 | 0.63 | 3000 | 4.3822 |
| 4.3549 | 0.84 | 4000 | 4.2353 |
| 4.1914 | 1.05 | 5000 | 4.1234 |
| 3.9985 | 1.26 | 6000 | 4.0512 |
| 3.9496 | 1.47 | 7000 | 3.9737 |
| 3.9029 | 1.68 | 8000 | 3.9040 |
| 3.8636 | 1.89 | 9000 | 3.8523 |
| 3.7011 | 2.1 | 10000 | 3.8414 |
| 3.5776 | 2.31 | 11000 | 3.8034 |
| 3.5683 | 2.52 | 12000 | 3.7755 |
| 3.5686 | 2.73 | 13000 | 3.7375 |
| 3.5352 | 2.94 | 14000 | 3.7042 |
| 3.3404 | 3.15 | 15000 | 3.7406 |
| 3.2763 | 3.36 | 16000 | 3.7177 |
| 3.2792 | 3.56 | 17000 | 3.7004 |
| 3.2808 | 3.77 | 18000 | 3.6864 |
| 3.2816 | 3.98 | 19000 | 3.6639 |
| 3.0586 | 4.19 | 20000 | 3.7184 |
| 3.0485 | 4.4 | 21000 | 3.7085 |
| 3.0446 | 4.61 | 22000 | 3.7014 |
| 3.0407 | 4.82 | 23000 | 3.6959 |
### Framework versions
- Transformers 4.39.1
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2
|