update model card README.md

README.md

@@ -1,20 +1,67 @@
 ---
-library_name: peft
+base_model: meta-llama/Llama-2-7b-hf
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+- f1
+model-index:
+- name: Llama-2-7b-hf-finetuned-mrpc-v0.4
+  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-2-7b-hf-finetuned-mrpc-v0.4
+
+This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5492
+- Accuracy: 0.7402
+- F1: 0.8251
+
+## 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: True
-- load_in_4bit: False
-- 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: fp4
-- bnb_4bit_use_double_quant: False
-- bnb_4bit_compute_dtype: float32
-### Framework versions
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| No log        | 1.0   | 230  | 0.6542          | 0.6446   | 0.7695 |
+| No log        | 2.0   | 460  | 0.5938          | 0.6912   | 0.7968 |
+| 0.6489        | 3.0   | 690  | 0.5694          | 0.7230   | 0.8151 |
+| 0.6489        | 4.0   | 920  | 0.5503          | 0.7230   | 0.8138 |
+| 0.5299        | 5.0   | 1150 | 0.5492          | 0.7402   | 0.8251 |
+
+
+### Framework versions
 
-- PEFT 0.4.0
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3