SimoneJLaudani/trainer3

1---2license: apache-2.03base_model: distilbert-base-uncased4tags:5- generated_from_trainer6metrics:7- precision8- recall9- f110- accuracy11model-index:12- name: trainer313  results: []14---15 16<!-- This model card has been generated automatically according to the information the Trainer had access to. You17should probably proofread and complete it, then remove this comment. -->18 19# trainer320 21This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.22It achieves the following results on the evaluation set:23- Loss: 0.537724- Precision: 0.830625- Recall: 0.827226- F1: 0.827427- Accuracy: 0.827228 29## Model description30 31More information needed32 33## Intended uses & limitations34 35More information needed36 37## Training and evaluation data38 39More information needed40 41## Training procedure42 43### Training hyperparameters44 45The following hyperparameters were used during training:46- learning_rate: 5e-0547- train_batch_size: 6448- eval_batch_size: 6449- seed: 4250- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0851- lr_scheduler_type: linear52- num_epochs: 553 54### Training results55 56| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |57|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|58| 1.0119        | 2.2222 | 100  | 0.6056          | 0.8215    | 0.8131 | 0.8129 | 0.8131   |59| 0.229         | 4.4444 | 200  | 0.5377          | 0.8306    | 0.8272 | 0.8274 | 0.8272   |60 61 62### Framework versions63 64- Transformers 4.40.065- Pytorch 2.2.1+cu12166- Datasets 2.19.067- Tokenizers 0.19.168