update model card README.md

README.md

@@ -1,20 +1,72 @@
 ---
-library_name: peft
+base_model: meta-llama/Llama-2-13b-chat-hf
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: llama-2-13b-reward-oasst1
+  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. -->
+
+# llama-2-13b-reward-oasst1
+
+This model is a fine-tuned version of [meta-llama/Llama-2-13b-chat-hf](https://huggingface.co/meta-llama/Llama-2-13b-chat-hf) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4810
+- Accuracy: 0.7869
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
 ## Training procedure
 
+### Training hyperparameters
 
-The following `bitsandbytes` quantization config was used during training:
-- load_in_8bit: False
-- load_in_4bit: True
-- llm_int8_threshold: 6.0
-- llm_int8_skip_modules: None
-- llm_int8_enable_fp32_cpu_offload: False
-- llm_int8_has_fp16_weight: False
-- bnb_4bit_quant_type: nf4
-- bnb_4bit_use_double_quant: False
-- bnb_4bit_compute_dtype: float16
-### Framework versions
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5602        | 0.08  | 250  | 0.5436          | 0.7388   |
+| 0.6166        | 0.17  | 500  | 0.5340          | 0.7468   |
+| 0.6545        | 0.25  | 750  | 0.4899          | 0.7644   |
+| 0.5635        | 0.33  | 1000 | 0.4877          | 0.7532   |
+| 0.5933        | 0.42  | 1250 | 0.4930          | 0.7660   |
+| 0.5758        | 0.5   | 1500 | 0.4851          | 0.7740   |
+| 0.5212        | 0.58  | 1750 | 0.5021          | 0.7788   |
+| 0.5251        | 0.67  | 2000 | 0.4893          | 0.7804   |
+| 0.5145        | 0.75  | 2250 | 0.4924          | 0.7853   |
+| 0.5085        | 0.83  | 2500 | 0.4934          | 0.7853   |
+| 0.617         | 0.92  | 2750 | 0.4803          | 0.7821   |
+| 0.5525        | 1.0   | 3000 | 0.4810          | 0.7869   |
+
+
+### Framework versions
 
-- PEFT 0.5.0.dev0
+- Transformers 4.32.0.dev0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.0
+- Tokenizers 0.13.3