complete: train_size: {train_size}, batch_size: {batch_size}, per_epoch_steps: {per_epoch_steps}, epochs: {epochs}, epoch_total_steps: {epoch_total_steps}
6e16d2c
verified
| license: gemma | |
| base_model: google/gemma-2b | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - rouge | |
| model-index: | |
| - name: gemma-2b-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. --> | |
| # gemma-2b-coedit | |
| This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.7456 | |
| - Rouge1: 0.5006 | |
| - Rouge2: 0.3991 | |
| - Rougel: 0.4788 | |
| - Rougelsum: 0.4786 | |
| - Sacreblue: 20.7764 | |
| - Memory Used: 79283.5 | |
| - Cuda Allocated: 9625.1006 | |
| - Cuda Reserved: 73102.0 | |
| - Ram Usage: 10024.6953 | |
| - Em: 0.0 | |
| - Gen Len: 101.5333 | |
| ## 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: 8 | |
| - 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 | | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:---------:|:-----------:|:--------------:|:-------------:|:----------:|:---:|:--------:| | |
| | 0.5426 | 0.22 | 100 | 0.7076 | 0.3807 | 0.297 | 0.3623 | 0.3621 | 18.8513 | 69159.5 | 9625.1431 | 62980.0 | 5073.7852 | 0.0 | 101.5333 | | |
| | 0.5051 | 0.44 | 200 | 0.6849 | 0.4094 | 0.3207 | 0.3907 | 0.3905 | 21.1175 | 67317.5 | 9625.1196 | 61138.0 | 5067.1328 | 0.0 | 101.5333 | | |
| | 0.4909 | 0.66 | 300 | 0.6735 | 0.4943 | 0.3926 | 0.473 | 0.4729 | 11.0979 | 67319.5 | 9625.1182 | 61138.0 | 9820.3711 | 0.0 | 101.5333 | | |
| | 0.4804 | 0.88 | 400 | 0.6672 | 0.4995 | 0.4004 | 0.4796 | 0.4795 | 24.1464 | 67319.5 | 9625.1079 | 61138.0 | 9803.6172 | 0.0 | 101.5333 | | |
| | 0.2842 | 1.1 | 500 | 0.7475 | 0.5011 | 0.3995 | 0.4792 | 0.4792 | 27.3521 | 79283.5 | 9625.0977 | 73102.0 | 9845.9766 | 0.0 | 101.5333 | | |
| | 0.2471 | 1.32 | 600 | 0.7447 | 0.4908 | 0.3906 | 0.4694 | 0.4693 | 24.0058 | 79283.5 | 9625.1123 | 73102.0 | 9916.7539 | 0.0 | 101.5333 | | |
| | 0.2422 | 1.54 | 700 | 0.7361 | 0.4967 | 0.3954 | 0.4749 | 0.4749 | 21.4519 | 79283.5 | 9625.1196 | 73102.0 | 9910.2695 | 0.0 | 101.5333 | | |
| | 0.2354 | 1.76 | 800 | 0.7443 | 0.4882 | 0.3882 | 0.467 | 0.4669 | 19.4531 | 79283.5 | 9625.124 | 73102.0 | 10050.582 | 0.0 | 101.5333 | | |
| | 0.2334 | 1.98 | 900 | 0.7456 | 0.5006 | 0.3991 | 0.4788 | 0.4786 | 20.7764 | 79283.5 | 9625.1006 | 73102.0 | 10024.6953 | 0.0 | 101.5333 | | |
| ### Framework versions | |
| - Transformers 4.39.3 | |
| - Pytorch 2.2.2 | |
| - Datasets 2.18.0 | |
| - Tokenizers 0.15.2 | |