gArthur98/Greg-Sentiment-classifier

1---2license: mit3base_model: microsoft/MiniLM-L12-H384-uncased4tags:5- generated_from_trainer6metrics:7- f18model-index:9- name: Greg-Sentiment-classifier10  results: []11---12 13<!-- This model card has been generated automatically according to the information the Trainer had access to. You14should probably proofread and complete it, then remove this comment. -->15 16# Greg-Sentiment-classifier17 18This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on an unknown dataset.19It achieves the following results on the evaluation set:20- Loss: 0.836821- F1: 0.656422 23## Model description24 25More information needed26 27## Intended uses & limitations28 29More information needed30 31## Training and evaluation data32 33More information needed34 35## Training procedure36 37### Training hyperparameters38 39The following hyperparameters were used during training:40- learning_rate: 5e-0541- train_batch_size: 842- eval_batch_size: 843- seed: 4244- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0845- lr_scheduler_type: linear46- num_epochs: 347 48### Training results49 50| Training Loss | Epoch | Step | Validation Loss | F1     |51|:-------------:|:-----:|:----:|:---------------:|:------:|52| 0.9048        | 0.5   | 500  | 0.8963          | 0.6318 |53| 0.8732        | 1.0   | 1000 | 0.8611          | 0.6437 |54| 0.8592        | 1.5   | 1500 | 0.9093          | 0.6486 |55| 0.8314        | 2.01  | 2000 | 0.8242          | 0.6542 |56| 0.8114        | 2.51  | 2500 | 0.8368          | 0.6564 |57 58 59### Framework versions60 61- Transformers 4.31.062- Pytorch 2.0.1+cu11863- Datasets 2.13.164- Tokenizers 0.13.365