File size: 2,836 Bytes
8b83c06 |
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 |
---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: N_roberta_imdb_padding70model
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
split: test
args: plain_text
metrics:
- name: Accuracy
type: accuracy
value: 0.95056
---
<!-- 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. -->
# N_roberta_imdb_padding70model
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4584
- Accuracy: 0.9506
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2111 | 1.0 | 1563 | 0.1864 | 0.9412 |
| 0.1628 | 2.0 | 3126 | 0.1973 | 0.9474 |
| 0.1178 | 3.0 | 4689 | 0.3140 | 0.9406 |
| 0.0745 | 4.0 | 6252 | 0.2698 | 0.9469 |
| 0.057 | 5.0 | 7815 | 0.3568 | 0.9424 |
| 0.0478 | 6.0 | 9378 | 0.3114 | 0.9477 |
| 0.0281 | 7.0 | 10941 | 0.3123 | 0.9491 |
| 0.0269 | 8.0 | 12504 | 0.3732 | 0.9464 |
| 0.0169 | 9.0 | 14067 | 0.4043 | 0.9466 |
| 0.0156 | 10.0 | 15630 | 0.3296 | 0.9480 |
| 0.0186 | 11.0 | 17193 | 0.4413 | 0.9466 |
| 0.015 | 12.0 | 18756 | 0.3944 | 0.9488 |
| 0.0091 | 13.0 | 20319 | 0.4310 | 0.9481 |
| 0.0061 | 14.0 | 21882 | 0.4363 | 0.9506 |
| 0.0073 | 15.0 | 23445 | 0.4315 | 0.9496 |
| 0.003 | 16.0 | 25008 | 0.4623 | 0.9499 |
| 0.0048 | 17.0 | 26571 | 0.4589 | 0.9494 |
| 0.0 | 18.0 | 28134 | 0.4556 | 0.9504 |
| 0.0028 | 19.0 | 29697 | 0.4608 | 0.9509 |
| 0.0013 | 20.0 | 31260 | 0.4584 | 0.9506 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
|