End of training

README.md

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+---
+license: other
+library_name: peft
+tags:
+- trl
+- sft
+- generated_from_trainer
+base_model: google/gemma-7b-it
+model-index:
+- name: gemma-7b-it-dolly-15k-japanese-brainstorming-ipo
+  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-7b-it-dolly-15k-japanese-brainstorming-ipo
+
+This model is a fine-tuned version of [google/gemma-7b-it](https://huggingface.co/google/gemma-7b-it) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.4864
+- Rouge Scores: {'rouge1': 0.8349379511354852, 'rouge2': 0.7274477012465996, 'rougeL': 0.8017731965466872, 'rougeLsum': 0.8347274626949961}
+- Bleu Scores: [0.8344549267092076, 0.7702670675251023, 0.7108107057859971, 0.6501643333897235]
+- Gen Len: 241.8588
+
+## 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: 0.0002
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge Scores                                                                                                                | Bleu Scores                                                                      | Gen Len  |
+|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------:|:--------:|
+| 2.6263        | 1.0   | 398  | 2.3289          | {'rouge1': 0.8429091284800581, 'rouge2': 0.6936436106699162, 'rougeL': 0.8148324021885509, 'rougeLsum': 0.8436115528203997} | [0.8182599825705432, 0.7573989130361584, 0.6993616529579798, 0.6397083137823109] | 241.8588 |
+| 1.4454        | 2.0   | 796  | 2.2673          | {'rouge1': 0.8676191825821662, 'rouge2': 0.7714826591897748, 'rougeL': 0.8384600375456672, 'rougeLsum': 0.8676504211460437} | [0.838231259049653, 0.7749860292910674, 0.715811357776676, 0.6553787760578684]   | 241.8588 |
+| 0.6829        | 3.0   | 1194 | 2.4864          | {'rouge1': 0.8349379511354852, 'rouge2': 0.7274477012465996, 'rougeL': 0.8017731965466872, 'rougeLsum': 0.8347274626949961} | [0.8344549267092076, 0.7702670675251023, 0.7108107057859971, 0.6501643333897235] | 241.8588 |
+
+
+### Framework versions
+
+- PEFT 0.8.2
+- Transformers 4.39.0.dev0
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.2.dev0
+- Tokenizers 0.15.2

runs/Feb24_14-52-58_dbc3db1324c3/events.out.tfevents.1708786430.dbc3db1324c3.4675.0

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