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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: xtremedistil-emotion
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: emotion
type: emotion
args: default
metrics:
- type: accuracy
value: 0.9265
name: Accuracy
- task:
type: text-classification
name: Text Classification
dataset:
name: emotion
type: emotion
config: default
split: test
metrics:
- type: accuracy
value: 0.926
name: Accuracy
verified: true
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- type: precision
value: 0.8855308537052737
name: Precision Macro
verified: true
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- type: precision
value: 0.926
name: Precision Micro
verified: true
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- type: precision
value: 0.9281282413639949
name: Precision Weighted
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiODVlOTM3ODVhMWM0MjU4Mzg2OGNkYjc2ZmExODYzOWIzYjdlYzE4OWE0ZWI4ZjcxMjJiMGJiMzdhN2RiNTdlNiIsInZlcnNpb24iOjF9.8-HhpgKNt3nTcblnes4KxzsD7Xot3C6Rldp4463H9gaUNBxHcH19mFcpaSaDT_L3mYqetcW891jyNrHoATzuAg
- type: recall
value: 0.8969894921856228
name: Recall Macro
verified: true
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- type: recall
value: 0.926
name: Recall Micro
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZjAxMTUzMmI1YmMwYTBmYzFmM2E3Y2NiY2M4Njc4ZDc1ZWRhMTMyMDVhMWNiMGQ1ZDRiMjcwYmQ0MDAxZmI3NSIsInZlcnNpb24iOjF9.OphK_nR4EkaAUGMdZDq1rP_oBivfLHQhE7XY1HP9izhDd6rV5KobTrSdoxVCHGUtjOm1M6eZqI_1rPpunoCqDQ
- type: recall
value: 0.926
name: Recall Weighted
verified: true
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- type: f1
value: 0.8903400738742536
name: F1 Macro
verified: true
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- type: f1
value: 0.926
name: F1 Micro
verified: true
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- type: f1
value: 0.9265018282649476
name: F1 Weighted
verified: true
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- type: loss
value: 0.2258329838514328
name: loss
verified: true
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---
# 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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