File size: 2,379 Bytes
ff36ade 191c1bc ff36ade |
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 |
---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-tiny-8l-10M
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. -->
# roberta-tiny-8l-10M
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 7.3389
- Accuracy: 0.0516
## 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
- gradient_accumulation_steps: 32
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- num_epochs: 100.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 7.8102 | 1.04 | 50 | 7.3747 | 0.0514 |
| 7.805 | 2.08 | 100 | 7.3699 | 0.0517 |
| 7.7907 | 3.12 | 150 | 7.3595 | 0.0517 |
| 7.7838 | 4.16 | 200 | 7.3617 | 0.0514 |
| 7.7706 | 5.21 | 250 | 7.3586 | 0.0514 |
| 7.2933 | 6.25 | 300 | 7.3566 | 0.0513 |
| 7.2932 | 7.29 | 350 | 7.3527 | 0.0516 |
| 7.2986 | 8.33 | 400 | 7.3561 | 0.0516 |
| 7.289 | 9.37 | 450 | 7.3495 | 0.0515 |
| 7.2879 | 10.41 | 500 | 7.3455 | 0.0514 |
| 7.276 | 11.45 | 550 | 7.3477 | 0.0513 |
| 7.3072 | 12.49 | 600 | 7.3446 | 0.0516 |
| 7.2978 | 13.53 | 650 | 7.3463 | 0.0514 |
| 7.2857 | 14.58 | 700 | 7.3426 | 0.0515 |
| 7.2868 | 15.62 | 750 | 7.3438 | 0.0515 |
| 7.2973 | 16.66 | 800 | 7.3442 | 0.0517 |
| 7.2988 | 17.7 | 850 | 7.3437 | 0.0512 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.11.0+cu113
- Datasets 2.6.1
- Tokenizers 0.12.1
|