jetmoe
/

jetmoe-8b-chat

@@ -1,199 +1,74 @@
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 ---
+base_model: jetmoe/jetmoe-8b-sft
+tags:
+- alignment-handbook
+- generated_from_trainer
+datasets:
+- HuggingFaceH4/ultrafeedback_binarized
+model-index:
+- name: jetmoe-8b-chat
+  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. -->
+# jetmoe-8b-chat
+This model is a fine-tuned version of [jetmoe-8b-sft](https://huggingface.co/jetmoe/jetmoe-8b-sft) on the HuggingFaceH4/ultrafeedback_binarized dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6372
+- Rewards/chosen: -0.0901
+- Rewards/rejected: -0.2250
+- Rewards/accuracies: 0.7148
+- Rewards/margins: 0.1349
+- Logps/rejected: -289.3396
+- Logps/chosen: -286.2378
+- Logits/rejected: -2.9020
+- Logits/chosen: -2.9443
+## 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: 4
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 4
+- 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
+| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.6664        | 0.42  | 200  | 0.6622          | -0.0185        | -0.0869          | 0.6997             | 0.0684          | -275.5274      | -279.0778    | -2.9127         | -2.9572       |
+| 0.6428        | 0.84  | 400  | 0.6372          | -0.0901        | -0.2250          | 0.7148             | 0.1349          | -289.3396      | -286.2378    | -2.9020         | -2.9443       |
+### Framework versions
+- Transformers 4.39.0.dev0
+- Pytorch 2.1.2
+- Datasets 2.14.6
+- Tokenizers 0.15.2