metadata
license: mit
base_model: microsoft/xtremedistil-l6-h384-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xtremedistil-l6-h384-uncased-v1.1
results: []
xtremedistil-l6-h384-uncased-v1.1
This model is a fine-tuned version of microsoft/xtremedistil-l6-h384-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5278
- F1 Macro: 0.6999
- F1 Micro: 0.7000
- Accuracy Balanced: 0.7017
- Accuracy: 0.7000
- Precision Macro: 0.7009
- Recall Macro: 0.7017
- Precision Micro: 0.7000
- Recall Micro: 0.7000
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: 128
- seed: 40
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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
| Datasets | asadfgglie/nli-zh-tw-all/test | asadfgglie/BanBan_2024-10-17-facial_expressions-nli/test | eval_dataset | test_dataset |
|---|---|---|---|---|
| eval_loss | 0.511 | 0.701 | 0.539 | 0.528 |
| eval_f1_macro | 0.717 | 0.488 | 0.684 | 0.7 |
| eval_f1_micro | 0.718 | 0.506 | 0.684 | 0.7 |
| eval_accuracy_balanced | 0.719 | 0.501 | 0.687 | 0.702 |
| eval_accuracy | 0.718 | 0.506 | 0.684 | 0.7 |
| eval_precision_macro | 0.718 | 0.501 | 0.686 | 0.701 |
| eval_recall_macro | 0.719 | 0.501 | 0.687 | 0.702 |
| eval_precision_micro | 0.718 | 0.506 | 0.684 | 0.7 |
| eval_recall_micro | 0.718 | 0.506 | 0.684 | 0.7 |
| eval_runtime | 8.805 | 0.188 | 1.873 | 7.442 |
| eval_samples_per_second | 965.397 | 5039.361 | 1008.401 | 1015.398 |
| eval_steps_per_second | 7.61 | 42.616 | 8.007 | 8.062 |
| Size of dataset | 8500 | 946 | 1889 | 7557 |
eval result
| Datasets | asadfgglie/nli-zh-tw-all/test | asadfgglie/BanBan_2024-10-17-facial_expressions-nli/test | eval_dataset | test_dataset |
|---|---|---|---|---|
| eval_loss | 0.511 | 0.701 | 0.539 | 0.528 |
| eval_f1_macro | 0.717 | 0.488 | 0.684 | 0.7 |
| eval_f1_micro | 0.718 | 0.506 | 0.684 | 0.7 |
| eval_accuracy_balanced | 0.719 | 0.501 | 0.687 | 0.702 |
| eval_accuracy | 0.718 | 0.506 | 0.684 | 0.7 |
| eval_precision_macro | 0.718 | 0.501 | 0.686 | 0.701 |
| eval_recall_macro | 0.719 | 0.501 | 0.687 | 0.702 |
| eval_precision_micro | 0.718 | 0.506 | 0.684 | 0.7 |
| eval_recall_micro | 0.718 | 0.506 | 0.684 | 0.7 |
| eval_runtime | 8.405 | 0.176 | 1.864 | 7.407 |
| eval_samples_per_second | 1011.367 | 5358.555 | 1013.595 | 1020.275 |
| eval_steps_per_second | 7.972 | 45.315 | 8.049 | 8.101 |
| epoch | 3.0 | 3.0 | 3.0 | 3.0 |
| Size of dataset | 8500 | 946 | 1889 | 7557 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.5.1+cu121
- Datasets 2.14.7
- Tokenizers 0.13.3