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---
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
---
# 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>
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