|
--- |
|
language: |
|
- en |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
- BERT |
|
datasets: |
|
- postbot/multi-emails-hq |
|
metrics: |
|
- accuracy |
|
pipeline_tag: fill-mask |
|
widget: |
|
- text: Can you please send me the [MASK] by the end of the day? |
|
example_title: end of day |
|
- text: I hope this email finds you well. I wanted to follow up on our [MASK] yesterday. |
|
example_title: follow-up |
|
- text: The meeting has been rescheduled to [MASK]. |
|
example_title: reschedule |
|
- text: Please let me know if you need any further [MASK] regarding the project. |
|
example_title: further help |
|
- text: I appreciate your prompt response to my previous email. Can you provide an |
|
update on the [MASK] by tomorrow? |
|
example_title: provide update |
|
- text: Paris is the [MASK] of France. |
|
example_title: paris (default) |
|
- text: The goal of life is [MASK]. |
|
example_title: goal of life (default) |
|
base_model: google/bert_uncased_L-2_H-256_A-4 |
|
model-index: |
|
- name: bert_uncased_L-2_H-256_A-4-mlm-multi-emails-hq |
|
results: [] |
|
--- |
|
|
|
|
|
# bert_uncased_L-2_H-256_A-4-mlm-multi-emails-hq |
|
|
|
This model is a fine-tuned version of [google/bert_uncased_L-2_H-256_A-4](https://huggingface.co/google/bert_uncased_L-2_H-256_A-4) on the `postbot/multi-emails-hq` dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.4596 |
|
- Accuracy: 0.5642 |
|
|
|
## Model description |
|
|
|
This is a ~40MB version of BERT finetuned on an MLM task on email data. |
|
|
|
## Intended uses & limitations |
|
|
|
- this is mostly a test/example |
|
|
|
## Training and evaluation data |
|
|
|
More information needed |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 0.0003 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- gradient_accumulation_steps: 16 |
|
- total_train_batch_size: 128 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_ratio: 0.05 |
|
- num_epochs: 8.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 3.097 | 0.99 | 141 | 2.8195 | 0.5180 | |
|
| 2.9097 | 1.99 | 282 | 2.6704 | 0.5367 | |
|
| 2.8335 | 2.99 | 423 | 2.5764 | 0.5485 | |
|
| 2.7433 | 3.99 | 564 | 2.5213 | 0.5563 | |
|
| 2.6828 | 4.99 | 705 | 2.4667 | 0.5641 | |
|
| 2.666 | 5.99 | 846 | 2.4688 | 0.5642 | |
|
| 2.6517 | 6.99 | 987 | 2.4452 | 0.5679 | |
|
| 2.6309 | 7.99 | 1128 | 2.4596 | 0.5642 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.27.0.dev0 |
|
- Pytorch 2.0.0.dev20230129+cu118 |
|
- Datasets 2.8.0 |
|
- Tokenizers 0.13.1 |
