---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: xtremedistil-emotion
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: emotion
      type: emotion
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9265
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: emotion
      type: emotion
      config: default
      split: test
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.926
      verified: true
    - name: Precision Macro
      type: precision
      value: 0.8855308537052737
      verified: true
    - name: Precision Micro
      type: precision
      value: 0.926
      verified: true
    - name: Precision Weighted
      type: precision
      value: 0.9281282413639949
      verified: true
    - name: Recall Macro
      type: recall
      value: 0.8969894921856228
      verified: true
    - name: Recall Micro
      type: recall
      value: 0.926
      verified: true
    - name: Recall Weighted
      type: recall
      value: 0.926
      verified: true
    - name: F1 Macro
      type: f1
      value: 0.8903400738742536
      verified: true
    - name: F1 Micro
      type: f1
      value: 0.926
      verified: true
    - name: F1 Weighted
      type: f1
      value: 0.9265018282649476
      verified: true
    - name: loss
      type: loss
      value: 0.2258329838514328
      verified: true
---

# xtremedistil-emotion
This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-uncased](https://huggingface.co/microsoft/xtremedistil-l6-h256-uncased) on the emotion dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.9265


### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 128
- eval_batch_size: 8
- seed: 42
- num_epochs: 24

### Training results
<pre>
Epoch	Training Loss	Validation Loss	Accuracy
1	No log	1.238589	0.609000
2	No log	0.934423	0.714000
3	No log	0.768701	0.742000
4	1.074800	0.638208	0.805500
5	1.074800	0.551363	0.851500
6	1.074800	0.476291	0.875500
7	1.074800	0.427313	0.883500
8	0.531500	0.392633	0.886000
9	0.531500	0.357979	0.892000
10	0.531500	0.330304	0.899500
11	0.531500	0.304529	0.907000
12	0.337200	0.287447	0.918000
13	0.337200	0.277067	0.921000
14	0.337200	0.259483	0.921000
15	0.337200	0.257564	0.916500
16	0.246200	0.241970	0.919500
17	0.246200	0.241537	0.921500
18	0.246200	0.235705	0.924500
19	0.246200	0.237325	0.920500
20	0.201400	0.229699	0.923500
21	0.201400	0.227426	0.923000
22	0.201400	0.228554	0.924000
23	0.201400	0.226941	0.925500
24	0.184300	0.225816	0.926500
</pre>