Model save

README.md

@@ -3,15 +3,11 @@ library_name: transformers
 license: apache-2.0
 base_model: mistralai/Mistral-7B-v0.3
 tags:
-- alignment-handbook
-- trl
-- sft
-- generated_from_trainer
 - trl
 - sft
 - generated_from_trainer
 datasets:
-- data/ift
+- generator
 model-index:
 - name: mistral-7b-ift
   results: []
@@ -22,9 +18,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 # mistral-7b-ift
 
-This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on the data/ift dataset.
+This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on the generator dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9144
+- Loss: 0.9529
 
 ## Model description
 
@@ -48,10 +44,10 @@ The following hyperparameters were used during training:
 - eval_batch_size: 8
 - seed: 42
 - distributed_type: multi-GPU
-- num_devices: 4
+- num_devices: 8
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 128
-- total_eval_batch_size: 32
+- total_train_batch_size: 256
+- 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
@@ -59,11 +55,11 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss |
-|:-------------:|:-----:|:----:|:---------------:|
-| 0.9502        | 1.0   | 911  | 0.9853          |
-| 0.8625        | 2.0   | 1822 | 0.9243          |
-| 0.8581        | 3.0   | 2733 | 0.9144          |
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.9643        | 0.9989 | 455  | 1.0198          |
+| 0.9077        | 2.0    | 911  | 0.9618          |
+| 0.8919        | 2.9967 | 1365 | 0.9529          |
 
 
 ### Framework versions

all_results.json

@@ -1,14 +1,9 @@
 {
-    "epoch": 3.0,
-    "eval_loss": 0.914355993270874,
-    "eval_runtime": 6.1247,
-    "eval_samples": 512,
-    "eval_samples_per_second": 43.758,
-    "eval_steps_per_second": 1.469,
-    "total_flos": 572182254059520.0,
-    "train_loss": 0.9187763968187508,
-    "train_runtime": 32723.3769,
+    "epoch": 2.996706915477497,
+    "total_flos": 571501770178560.0,
+    "train_loss": 0.9509169136648213,
+    "train_runtime": 15780.8295,
     "train_samples": 77486,
-    "train_samples_per_second": 10.687,
-    "train_steps_per_second": 0.084
+    "train_samples_per_second": 22.162,
+    "train_steps_per_second": 0.086
 }

train_results.json

@@ -1,9 +1,9 @@
 {
-    "epoch": 3.0,
-    "total_flos": 572182254059520.0,
-    "train_loss": 0.9187763968187508,
-    "train_runtime": 32723.3769,
+    "epoch": 2.996706915477497,
+    "total_flos": 571501770178560.0,
+    "train_loss": 0.9509169136648213,
+    "train_runtime": 15780.8295,
     "train_samples": 77486,
-    "train_samples_per_second": 10.687,
-    "train_steps_per_second": 0.084
+    "train_samples_per_second": 22.162,
+    "train_steps_per_second": 0.086
 }