File size: 2,463 Bytes
143f0de |
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 |
---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_base_uncased_amazon
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. -->
# bert_base_uncased_amazon
This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7916
- Accuracy: 0.7879
- F1 Macro: 0.7308
- F1 Micro: 0.7879
## 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: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 2.5476 | 0.26 | 50 | 2.4071 | 0.4967 | 0.3546 | 0.4967 |
| 1.7401 | 0.53 | 100 | 1.6470 | 0.6337 | 0.4899 | 0.6337 |
| 1.3223 | 0.79 | 150 | 1.2889 | 0.6897 | 0.5665 | 0.6897 |
| 1.1317 | 1.05 | 200 | 1.1047 | 0.7358 | 0.6577 | 0.7358 |
| 0.9137 | 1.32 | 250 | 0.9907 | 0.7536 | 0.6820 | 0.7536 |
| 0.9434 | 1.58 | 300 | 0.9264 | 0.7602 | 0.6896 | 0.7602 |
| 0.86 | 1.84 | 350 | 0.8729 | 0.7780 | 0.7135 | 0.7780 |
| 0.7567 | 2.11 | 400 | 0.8322 | 0.7859 | 0.7244 | 0.7859 |
| 0.7028 | 2.37 | 450 | 0.8130 | 0.7892 | 0.7339 | 0.7892 |
| 0.6842 | 2.63 | 500 | 0.8005 | 0.7892 | 0.7284 | 0.7892 |
| 0.6784 | 2.89 | 550 | 0.7916 | 0.7879 | 0.7308 | 0.7879 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|