Model save

README.md

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+---
+license: mit
+base_model: ShenaoZ/0.0001_ablation_iter_2
+tags:
+- trl
+- dpo
+- generated_from_trainer
+model-index:
+- name: 0.0001_ablation_iter_3
+  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. -->
+
+# 0.0001_ablation_iter_3
+
+This model is a fine-tuned version of [ShenaoZ/0.0001_ablation_iter_2](https://huggingface.co/ShenaoZ/0.0001_ablation_iter_2) on the None dataset.
+
+## 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: 5e-07
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 128
+- total_eval_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2+cu121
+- Datasets 2.14.6
+- Tokenizers 0.15.2

all_results.json

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+{
+    "epoch": 1.0,
+    "train_loss": 0.5938605962309448,
+    "train_runtime": 4590.1424,
+    "train_samples": 20378,
+    "train_samples_per_second": 4.44,
+    "train_steps_per_second": 0.035
+}

generation_config.json

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+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.36.2"
+}

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