|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: small-mlm-imdb |
|
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. --> |
|
|
|
# small-mlm-imdb |
|
|
|
This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.3673 |
|
|
|
## 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: 3e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: constant |
|
- num_epochs: 200 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:-----:|:---------------:| |
|
| 2.7542 | 0.16 | 500 | 2.5445 | |
|
| 2.6734 | 0.32 | 1000 | 2.5191 | |
|
| 2.6552 | 0.48 | 1500 | 2.4976 | |
|
| 2.6481 | 0.64 | 2000 | 2.4866 | |
|
| 2.6291 | 0.8 | 2500 | 2.4599 | |
|
| 2.6134 | 0.96 | 3000 | 2.4585 | |
|
| 2.5627 | 1.12 | 3500 | 2.4476 | |
|
| 2.5564 | 1.28 | 4000 | 2.4340 | |
|
| 2.5493 | 1.44 | 4500 | 2.4354 | |
|
| 2.5435 | 1.6 | 5000 | 2.4307 | |
|
| 2.5352 | 1.76 | 5500 | 2.4224 | |
|
| 2.5445 | 1.92 | 6000 | 2.4167 | |
|
| 2.5191 | 2.08 | 6500 | 2.4175 | |
|
| 2.5143 | 2.24 | 7000 | 2.4149 | |
|
| 2.5059 | 2.4 | 7500 | 2.4117 | |
|
| 2.4865 | 2.56 | 8000 | 2.4063 | |
|
| 2.5113 | 2.72 | 8500 | 2.3976 | |
|
| 2.5115 | 2.88 | 9000 | 2.3959 | |
|
| 2.485 | 3.04 | 9500 | 2.3917 | |
|
| 2.4652 | 3.2 | 10000 | 2.3908 | |
|
| 2.4569 | 3.36 | 10500 | 2.3877 | |
|
| 2.4706 | 3.52 | 11000 | 2.3836 | |
|
| 2.4375 | 3.68 | 11500 | 2.3870 | |
|
| 2.4556 | 3.84 | 12000 | 2.3819 | |
|
| 2.4487 | 4.0 | 12500 | 2.3842 | |
|
| 2.4233 | 4.16 | 13000 | 2.3731 | |
|
| 2.4238 | 4.32 | 13500 | 2.3801 | |
|
| 2.4051 | 4.48 | 14000 | 2.3809 | |
|
| 2.432 | 4.64 | 14500 | 2.3641 | |
|
| 2.428 | 4.8 | 15000 | 2.3686 | |
|
| 2.4248 | 4.96 | 15500 | 2.3741 | |
|
| 2.4109 | 5.12 | 16000 | 2.3673 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.1 |
|
- Pytorch 1.12.1 |
|
- Datasets 2.7.1 |
|
- Tokenizers 0.13.2 |
|
|
