update model card README.md

README.md

@@ -8,7 +8,6 @@ datasets:
 model-index:
 - name: falcon_40b_qlora_sql_r64
   results: []
-library_name: peft
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,12 +17,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [tiiuae/falcon-40b](https://huggingface.co/tiiuae/falcon-40b) on the spider dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 0.2048
-- eval_runtime: 241.57
-- eval_samples_per_second: 4.28
-- eval_steps_per_second: 0.538
-- epoch: 0.46
-- step: 200
+- Loss: 0.1260
 
 ## Model description
 
@@ -39,34 +33,32 @@ More information needed
 
 ## Training procedure
 
-
-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: True
-- bnb_4bit_compute_dtype: bfloat16
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0001
-- train_batch_size: 8
-- eval_batch_size: 8
+- train_batch_size: 4
+- eval_batch_size: 4
 - seed: 42
-- gradient_accumulation_steps: 2
+- gradient_accumulation_steps: 4
 - total_train_batch_size: 16
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 43.7
-- num_epochs: 3
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.1845        | 0.23  | 100  | 0.2542          |
+| 0.5572        | 0.46  | 200  | 0.2048          |
+| 0.0779        | 0.69  | 300  | 0.1761          |
+| 0.0581        | 0.91  | 400  | 0.1315          |
+
 
 ### Framework versions
 
-- PEFT 0.5.0.dev0
 - Transformers 4.32.0.dev0
 - Pytorch 2.0.1+cu118
 - Datasets 2.13.1