---
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: []
---

<!-- 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-h384-uncased-v1.1

This model is a fine-tuned version of [microsoft/xtremedistil-l6-h384-uncased](https://huggingface.co/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