|
--- |
|
license: mit |
|
base_model: microsoft/xtremedistil-l6-h256-uncased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: xtremedistil-l6-h256-uncased-zeroshot-v1.1-none |
|
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. --> |
|
|
|
# xtremedistil-l6-h256-uncased-zeroshot-v1.1-none |
|
|
|
This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-uncased](https://huggingface.co/microsoft/xtremedistil-l6-h256-uncased) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1992 |
|
- F1 Macro: 0.5455 |
|
- F1 Micro: 0.6194 |
|
- Accuracy Balanced: 0.5960 |
|
- Accuracy: 0.6194 |
|
- Precision Macro: 0.5566 |
|
- Recall Macro: 0.5960 |
|
- Precision Micro: 0.6194 |
|
- Recall Micro: 0.6194 |
|
|
|
## 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: 128 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.06 |
|
- num_epochs: 3 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:| |
|
| 0.3056 | 1.0 | 30790 | 0.4634 | 0.7791 | 0.8013 | 0.7757 | 0.8013 | 0.7832 | 0.7757 | 0.8013 | 0.8013 | |
|
| 0.2847 | 2.0 | 61580 | 0.4656 | 0.7826 | 0.8040 | 0.7797 | 0.8040 | 0.7859 | 0.7797 | 0.8040 | 0.8040 | |
|
| 0.2618 | 3.0 | 92370 | 0.4774 | 0.7848 | 0.8045 | 0.7841 | 0.8045 | 0.7856 | 0.7841 | 0.8045 | 0.8045 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.3 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.14.7 |
|
- Tokenizers 0.13.3 |
|
|