GhylB/Sentiment_Analysis_BERT_Based_MODEL

1---2license: apache-2.03tags:4- generated_from_trainer5model-index:6- name: Sentiment_Analysis_BERT_Based_MODEL7  results: []8---9 10<!-- This model card has been generated automatically according to the information the Trainer had access to. You11should probably proofread and complete it, then remove this comment. -->12 13# Sentiment_Analysis_BERT_Based_MODEL14 15This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.16It achieves the following results on the evaluation set:17- Loss: 0.595518- Rmse: 0.669519 20## Model description21 22More information needed23 24## Intended uses & limitations25 26More information needed27 28## Training and evaluation data29 30More information needed31 32## Training procedure33 34### Training hyperparameters35 36The following hyperparameters were used during training:37- learning_rate: 3e-0538- train_batch_size: 239- eval_batch_size: 240- seed: 4241- gradient_accumulation_steps: 1642- total_train_batch_size: 3243- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0844- lr_scheduler_type: linear45- lr_scheduler_warmup_steps: 50046- num_epochs: 1047- mixed_precision_training: Native AMP48 49### Training results50 51| Training Loss | Epoch | Step | Validation Loss | Rmse   |52|:-------------:|:-----:|:----:|:---------------:|:------:|53| 0.7508        | 2.0   | 500  | 0.5955          | 0.6695 |54| 0.3953        | 4.0   | 1000 | 0.7485          | 0.6605 |55| 0.1399        | 6.0   | 1500 | 1.0561          | 0.6703 |56| 0.0585        | 8.0   | 2000 | 1.3094          | 0.6525 |57| 0.0298        | 10.0  | 2500 | 1.4381          | 0.6673 |58 59 60### Framework versions61 62- Transformers 4.28.163- Pytorch 2.0.0+cu11864- Datasets 2.12.065- Tokenizers 0.13.366