complete: train_size: {train_size}, batch_size: {batch_size}, per_epoch_steps: {per_epoch_steps}, epochs: {epochs}, epoch_total_steps: {epoch_total_steps}
f21cbc1
verified
| license: mit | |
| base_model: microsoft/phi-2 | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - rouge | |
| model-index: | |
| - name: phi-2-coedit | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # phi-2-coedit | |
| This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.7388 | |
| - Rouge1: 0.5206 | |
| - Rouge2: 0.4123 | |
| - Rougel: 0.4979 | |
| - Rougelsum: 0.5032 | |
| - Sacreblue: 28.1346 | |
| - Memory Used: 81917.5 | |
| - Cuda Allocated: 10795.7861 | |
| - Cuda Reserved: 74746.0 | |
| - Ram Usage: 24042.6719 | |
| - Em: 0.0 | |
| - Gen Len: 120.6545 | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - learning_rate: 2e-05 | |
| - train_batch_size: 35 | |
| - eval_batch_size: 35 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 4 | |
| - total_train_batch_size: 140 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_steps: 1 | |
| - num_epochs: 2 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Sacreblue | Memory Used | Cuda Allocated | Cuda Reserved | Ram Usage | Em | Gen Len | | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:---------:|:-----------:|:--------------:|:-------------:|:----------:|:---:|:--------:| | |
| | 0.5716 | 0.22 | 100 | 0.7558 | 0.5041 | 0.3927 | 0.4809 | 0.4853 | 26.9798 | 81917.5 | 10795.811 | 74738.0 | 22888.4102 | 0.0 | 120.3347 | | |
| | 0.5407 | 0.44 | 200 | 0.7404 | 0.5241 | 0.4171 | 0.5013 | 0.5068 | 27.6806 | 81917.5 | 10795.814 | 74738.0 | 23733.9805 | 0.0 | 120.8277 | | |
| | 0.5324 | 0.66 | 300 | 0.7230 | 0.5176 | 0.4093 | 0.4947 | 0.5002 | 27.5145 | 81917.5 | 10795.8184 | 74738.0 | 23831.1484 | 0.0 | 120.576 | | |
| | 0.5107 | 0.88 | 400 | 0.7161 | 0.5256 | 0.4167 | 0.5042 | 0.5092 | 28.1274 | 81917.5 | 10795.7935 | 74738.0 | 23891.7891 | 0.0 | 120.5225 | | |
| | 0.4374 | 1.1 | 500 | 0.7495 | 0.5237 | 0.414 | 0.501 | 0.5059 | 28.0405 | 81917.5 | 10795.7861 | 74746.0 | 23922.043 | 0.0 | 120.3181 | | |
| | 0.3515 | 1.32 | 600 | 0.7418 | 0.5216 | 0.4133 | 0.499 | 0.5049 | 28.0528 | 81917.5 | 10795.7832 | 74746.0 | 23973.8164 | 0.0 | 120.6453 | | |
| | 0.3449 | 1.54 | 700 | 0.7386 | 0.5242 | 0.4163 | 0.5016 | 0.5075 | 28.3145 | 81917.5 | 10795.8066 | 74746.0 | 23950.1016 | 0.0 | 120.5367 | | |
| | 0.3375 | 1.76 | 800 | 0.7354 | 0.5194 | 0.4124 | 0.4973 | 0.5025 | 28.0252 | 81917.5 | 10795.814 | 74746.0 | 23931.0 | 0.0 | 120.6476 | | |
| | 0.3373 | 1.98 | 900 | 0.7388 | 0.5206 | 0.4123 | 0.4979 | 0.5032 | 28.1346 | 81917.5 | 10795.7861 | 74746.0 | 24042.6719 | 0.0 | 120.6545 | | |
| ### Framework versions | |
| - Transformers 4.39.3 | |
| - Pytorch 2.2.2 | |
| - Datasets 2.18.0 | |
| - Tokenizers 0.15.2 | |