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---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: electra-large-discriminator-nli-efl-tweeteval
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. -->
# electra-large-discriminator-nli-efl-tweeteval
This model is a fine-tuned version of [ynie/electra-large-discriminator-snli_mnli_fever_anli_R1_R2_R3-nli](https://huggingface.co/ynie/electra-large-discriminator-snli_mnli_fever_anli_R1_R2_R3-nli) on the None dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.7943
- F1: 0.7872
- Loss: 0.3004
## 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: 1e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- 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 | Accuracy | F1 | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:------:|:---------------:|
| 0.4384 | 1.0 | 163 | 0.7444 | 0.7308 | 0.3962 |
| 0.3447 | 2.0 | 326 | 0.7659 | 0.7552 | 0.3410 |
| 0.3057 | 3.0 | 489 | 0.7750 | 0.7688 | 0.3234 |
| 0.287 | 4.0 | 652 | 0.7857 | 0.7779 | 0.3069 |
| 0.2742 | 5.0 | 815 | 0.7887 | 0.7822 | 0.3030 |
| 0.2676 | 6.0 | 978 | 0.7939 | 0.7851 | 0.2982 |
| 0.2585 | 7.0 | 1141 | 0.7909 | 0.7822 | 0.3002 |
| 0.2526 | 8.0 | 1304 | 0.7943 | 0.7876 | 0.3052 |
| 0.2479 | 9.0 | 1467 | 0.7939 | 0.7847 | 0.2997 |
| 0.2451 | 10.0 | 1630 | 0.7956 | 0.7873 | 0.3014 |
| 0.2397 | 11.0 | 1793 | 0.7943 | 0.7872 | 0.3004 |
### Framework versions
- Transformers 4.16.2
- Pytorch 1.12.0.dev20220417
- Datasets 2.1.0
- Tokenizers 0.10.3