End of training

README.md

@@ -5,8 +5,6 @@ tags:
 - generated_from_trainer
 datasets:
 - truthful_qa
-metrics:
-- accuracy
 model-index:
 - name: vicuna_mc_finetune
   results: []
@@ -18,9 +16,6 @@ should probably proofread and complete it, then remove this comment. -->
 # vicuna_mc_finetune
 
 This model is a fine-tuned version of [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) on the truthful_qa dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.8867
-- Accuracy: 0.2378
 
 ## Model description
 
@@ -40,7 +35,7 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0001
-- train_batch_size: 6
+- train_batch_size: 4
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
@@ -51,28 +46,6 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.7307        | 1.0   | 109  | 1.5327          | 0.4024   |
-| 1.4519        | 2.0   | 218  | 1.2341          | 0.7073   |
-| 0.0207        | 3.0   | 327  | 2.2924          | 0.6280   |
-| 1.5647        | 4.0   | 436  | 1.9344          | 0.2256   |
-| 2.2047        | 5.0   | 545  | 1.9401          | 0.2256   |
-| 2.016         | 6.0   | 654  | 1.8888          | 0.2256   |
-| 1.625         | 7.0   | 763  | 1.9068          | 0.1768   |
-| 2.0002        | 8.0   | 872  | 1.8909          | 0.1951   |
-| 1.7906        | 9.0   | 981  | 1.8828          | 0.2195   |
-| 1.5295        | 10.0  | 1090 | 1.8967          | 0.2195   |
-| 1.7018        | 11.0  | 1199 | 1.8845          | 0.2378   |
-| 1.8412        | 12.0  | 1308 | 1.8808          | 0.2073   |
-| 2.4396        | 13.0  | 1417 | 1.8816          | 0.2012   |
-| 1.8643        | 14.0  | 1526 | 1.8827          | 0.2012   |
-| 1.7271        | 15.0  | 1635 | 1.8844          | 0.2256   |
-| 1.851         | 16.0  | 1744 | 1.8720          | 0.2134   |
-| 1.7633        | 17.0  | 1853 | 1.8786          | 0.2134   |
-| 2.6586        | 18.0  | 1962 | 1.8723          | 0.25     |
-| 2.0078        | 19.0  | 2071 | 1.8770          | 0.2439   |
-| 1.4072        | 20.0  | 2180 | 1.8867          | 0.2378   |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:eeb5782a8aab090924c2c1735a4022fc323843c570957228a909156a9fa6b943
-size 160283150
+oid sha256:e466fcfcc9ff9e06a42aff67a56b7e147058ba4c8d192cb8aef8fe74ecdf9b0f
+size 160069834

adapter_model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1ba45142d2f4bb16edc09dfc2e0a3c6dd6c719cee91d7dc4127aef524d2a9f38
+oid sha256:081a94ef255668ed7ae6e3f5dd83c8cbf1bedd20fbb9dd6729566d24aad2585c
 size 159967880

all_results.json

@@ -1,8 +1,8 @@
 {
     "epoch": 20.0,
-    "total_flos": 1.2663415269359616e+17,
-    "train_loss": 1.7466916341539105,
-    "train_runtime": 4318.1089,
-    "train_samples_per_second": 3.024,
-    "train_steps_per_second": 0.505
+    "total_flos": 1.4741018341490688e+17,
+    "train_loss": 0.13857511495262748,
+    "train_runtime": 5194.9579,
+    "train_samples_per_second": 2.514,
+    "train_steps_per_second": 0.631
 }

train_results.json

@@ -1,8 +1,8 @@
 {
     "epoch": 20.0,
-    "total_flos": 1.2663415269359616e+17,
-    "train_loss": 1.7466916341539105,
-    "train_runtime": 4318.1089,
-    "train_samples_per_second": 3.024,
-    "train_steps_per_second": 0.505
+    "total_flos": 1.4741018341490688e+17,
+    "train_loss": 0.13857511495262748,
+    "train_runtime": 5194.9579,
+    "train_samples_per_second": 2.514,
+    "train_steps_per_second": 0.631
 }