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-english-brainstorming
+  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-english-brainstorming
+
+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: 2.3974
+- Rouge Scores: {'rouge1': 0.8672818649395687, 'rouge2': 0.6454332350275582, 'rougeL': 0.6351345254871303, 'rougeLsum': 0.8672626398857906}
+- Bleu Scores: [0.8956480474494563, 0.8706364987273697, 0.8304269359390679, 0.785372823061285]
+- Gen Len: 170.6158
+
+## 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  |
+|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------:|:--------:|
+| 2.3012        | 1.0   | 398  | 2.0026          | {'rouge1': 0.8605967894222545, 'rouge2': 0.636131431928223, 'rougeL': 0.6291428969983008, 'rougeLsum': 0.860624331598749}   | [0.8793248327807496, 0.8543278363738773, 0.8139923136639805, 0.7687265678282116] | 170.5932 |
+| 1.2054        | 2.0   | 796  | 2.0260          | {'rouge1': 0.8587397434055452, 'rouge2': 0.6353005312218787, 'rougeL': 0.6345388735413529, 'rougeLsum': 0.8588818459220777} | [0.874882697664012, 0.8507131493229504, 0.8111205664503656, 0.7665706439816697]  | 170.6271 |
+| 0.519         | 3.0   | 1194 | 2.3974          | {'rouge1': 0.8672818649395687, 'rouge2': 0.6454332350275582, 'rougeL': 0.6351345254871303, 'rougeLsum': 0.8672626398857906} | [0.8956480474494563, 0.8706364987273697, 0.8304269359390679, 0.785372823061285]  | 170.6158 |
+
+
+### Framework versions
+
+- PEFT 0.9.1.dev0
+- Transformers 4.39.0.dev0
+- Pytorch 2.1.0+cu121
+- Datasets 2.18.1.dev0
+- Tokenizers 0.15.2

runs/Mar03_14-39-00_95f9060b6c3d/events.out.tfevents.1709476872.95f9060b6c3d.2927.0

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