MaVier19/zero-shot_text_classification_2

1---2license: mit3base_model: MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli4tags:5- generated_from_trainer6metrics:7- accuracy8- f19model-index:10- name: zero-shot_text_classification_211  results: []12---13 14<!-- This model card has been generated automatically according to the information the Trainer had access to. You15should probably proofread and complete it, then remove this comment. -->16 17# zero-shot_text_classification_218 19This model is a fine-tuned version of [MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli](https://huggingface.co/MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli) on an unknown dataset.20It achieves the following results on the evaluation set:21- Loss: 0.710722- Accuracy: 0.7723- F1: 0.769724 25## Model description26 27More information needed28 29## Intended uses & limitations30 31More information needed32 33## Training and evaluation data34 35More information needed36 37## Training procedure38 39### Training hyperparameters40 41The following hyperparameters were used during training:42- learning_rate: 5e-0543- train_batch_size: 844- eval_batch_size: 1645- seed: 4246- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0847- lr_scheduler_type: linear48- lr_scheduler_warmup_steps: 50049- num_epochs: 150 51### Training results52 53| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |54|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|55| 0.9528        | 1.0   | 1000 | 0.7107          | 0.77     | 0.7697 |56 57 58### Framework versions59 60- Transformers 4.35.261- Pytorch 2.1.0+cu12162- Datasets 2.15.063- Tokenizers 0.15.064