File size: 2,940 Bytes
f202794 b067546 f202794 b067546 f202794 b067546 f202794 b067546 f202794 |
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 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 |
---
license: mit
tags:
- generated_from_trainer
datasets:
- wikitext
metrics:
- accuracy
model-index:
- name: wikitext_roberta-base
results:
- task:
name: Masked Language Modeling
type: fill-mask
dataset:
name: wikitext wikitext-2-raw-v1
type: wikitext
args: wikitext-2-raw-v1
metrics:
- name: Accuracy
type: accuracy
value: 0.7371052344006119
---
<!-- 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. -->
# wikitext_roberta-base
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the wikitext wikitext-2-raw-v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2143
- Accuracy: 0.7371
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 20.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4175 | 0.99 | 37 | 1.3355 | 0.7194 |
| 1.438 | 1.99 | 74 | 1.2953 | 0.7249 |
| 1.4363 | 2.99 | 111 | 1.2759 | 0.7276 |
| 1.3391 | 3.99 | 148 | 1.2904 | 0.7252 |
| 1.3741 | 4.99 | 185 | 1.2621 | 0.7290 |
| 1.2771 | 5.99 | 222 | 1.2312 | 0.7353 |
| 1.287 | 6.99 | 259 | 1.2542 | 0.7289 |
| 1.29 | 7.99 | 296 | 1.2290 | 0.7345 |
| 1.2948 | 8.99 | 333 | 1.2537 | 0.7286 |
| 1.2741 | 9.99 | 370 | 1.2199 | 0.7354 |
| 1.2342 | 10.99 | 407 | 1.2520 | 0.7309 |
| 1.2199 | 11.99 | 444 | 1.2738 | 0.7260 |
| 1.206 | 12.99 | 481 | 1.2286 | 0.7335 |
| 1.221 | 13.99 | 518 | 1.2421 | 0.7327 |
| 1.2062 | 14.99 | 555 | 1.2402 | 0.7328 |
| 1.2305 | 15.99 | 592 | 1.2473 | 0.7308 |
| 1.2426 | 16.99 | 629 | 1.2250 | 0.7318 |
| 1.2096 | 17.99 | 666 | 1.2186 | 0.7353 |
| 1.1961 | 18.99 | 703 | 1.2214 | 0.7361 |
| 1.2136 | 19.99 | 740 | 1.2506 | 0.7311 |
### Framework versions
- Transformers 4.21.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.3.3.dev0
- Tokenizers 0.12.1
|