marklicata/M365_h2_Text_Processing_and_Summarization

1---2library_name: transformers3license: apache-2.04base_model: marklicata/M365_h1_base5tags:6- generated_from_trainer7model-index:8- name: M365_h2_Text_Processing_and_Summarization9  results: []10---11 12<!-- This model card has been generated automatically according to the information the Trainer had access to. You13should probably proofread and complete it, then remove this comment. -->14 15# M365_h2_Text_Processing_and_Summarization16 17This model is a fine-tuned version of [marklicata/M365_h1_base](https://huggingface.co/marklicata/M365_h1_base) on the None dataset.18It achieves the following results on the evaluation set:19- Loss: 0.028220 21## Model description22 23More information needed24 25## Intended uses & limitations26 27More information needed28 29## Training and evaluation data30 31More information needed32 33## Training procedure34 35### Training hyperparameters36 37The following hyperparameters were used during training:38- learning_rate: 5e-0539- train_batch_size: 840- eval_batch_size: 841- seed: 4242- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments43- lr_scheduler_type: linear44- num_epochs: 3.045 46### Training results47 48| Training Loss | Epoch | Step | Validation Loss |49|:-------------:|:-----:|:----:|:---------------:|50| 0.0469        | 1.0   | 1771 | 0.0380          |51| 0.0109        | 2.0   | 3542 | 0.0268          |52| 0.0029        | 3.0   | 5313 | 0.0282          |53 54 55### Framework versions56 57- Transformers 4.46.158- Pytorch 2.4.1+cu12159- Datasets 3.1.060- Tokenizers 0.20.161