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---
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: MiniLMv2-L12-H384-distilled-from-RoBERTa-Large-finetuned-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
metrics:
- name: Accuracy
type: accuracy
value: 0.9319354838709677
---
<!-- 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. -->
# MiniLMv2-L12-H384-distilled-from-RoBERTa-Large-finetuned-clinc
This model is a fine-tuned version of [nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large](https://huggingface.co/nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large) on the clinc_oos dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5252
- Accuracy: 0.9319
## 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: 0.0001
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 60 | 4.6555 | 0.1887 |
| No log | 2.0 | 120 | 3.8771 | 0.4784 |
| No log | 3.0 | 180 | 3.2507 | 0.7352 |
| 3.9668 | 4.0 | 240 | 2.7445 | 0.8365 |
| 3.9668 | 5.0 | 300 | 2.3475 | 0.8865 |
| 3.9668 | 6.0 | 360 | 2.0370 | 0.8926 |
| 3.9668 | 7.0 | 420 | 1.8099 | 0.9145 |
| 2.0924 | 8.0 | 480 | 1.6433 | 0.9190 |
| 2.0924 | 9.0 | 540 | 1.5563 | 0.9281 |
| 2.0924 | 10.0 | 600 | 1.5252 | 0.9319 |
### Framework versions
- Transformers 4.11.3
- Pytorch 1.11.0
- Datasets 1.16.1
- Tokenizers 0.10.3
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