End of training

README.md

@@ -21,14 +21,14 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [llava-hf/llava-1.5-7b-hf](https://huggingface.co/llava-hf/llava-1.5-7b-hf) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.1289
-- Bleu: 0.0753
-- Rouge1: 0.3197
-- Rouge2: 0.1315
-- Rougel: 0.2495
-- Bertscore Precision: 0.7078
-- Bertscore Recall: 0.7750
-- Bertscore F1: 0.7397
+- Loss: 0.0446
+- Bleu: 0.6353
+- Rouge1: 0.7885
+- Rouge2: 0.7889
+- Rougel: 0.7893
+- Bertscore Precision: 0.6807
+- Bertscore Recall: 0.7674
+- Bertscore F1: 0.7213
 
 ## Model description
 
@@ -55,14 +55,22 @@ The following hyperparameters were used during training:
 - total_train_batch_size: 128
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 20.0
+- num_epochs: 100.0
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Bleu   | Rouge1 | Rouge2 | Rougel | Bertscore Precision | Bertscore Recall | Bertscore F1 |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:-------------------:|:----------------:|:------------:|
-| 0.321         | 10.0  | 10   | 2.3171          | 0.0606 | 0.3028 | 0.1099 | 0.2281 | 0.7040              | 0.7734           | 0.7369       |
-| 0.2746        | 20.0  | 20   | 2.1289          | 0.0753 | 0.3197 | 0.1315 | 0.2495 | 0.7078              | 0.7750           | 0.7397       |
+| 0.3168        | 10.0  | 10   | 2.2001          | 0.0724 | 0.3123 | 0.1239 | 0.2433 | 0.7068              | 0.7777           | 0.7405       |
+| 0.2454        | 20.0  | 20   | 1.6882          | 0.1061 | 0.4044 | 0.1840 | 0.3274 | 0.7241              | 0.7794           | 0.7507       |
+| 0.1821        | 30.0  | 30   | 1.1567          | 0.1925 | 0.5281 | 0.2989 | 0.4593 | 0.7054              | 0.7756           | 0.7387       |
+| 0.109         | 40.0  | 40   | 0.5242          | 0.3915 | 0.6689 | 0.5316 | 0.6370 | 0.6878              | 0.7709           | 0.7268       |
+| 0.0378        | 50.0  | 50   | 0.1193          | 0.5971 | 0.7701 | 0.7585 | 0.7700 | 0.6839              | 0.7688           | 0.7237       |
+| 0.0098        | 60.0  | 60   | 0.0554          | 0.6254 | 0.7862 | 0.7867 | 0.7875 | 0.6799              | 0.7694           | 0.7217       |
+| 0.0064        | 70.0  | 70   | 0.0482          | 0.6329 | 0.7889 | 0.7890 | 0.7899 | 0.6798              | 0.7690           | 0.7215       |
+| 0.0059        | 80.0  | 80   | 0.0459          | 0.6331 | 0.7877 | 0.7877 | 0.7888 | 0.6777              | 0.7670           | 0.7194       |
+| 0.0057        | 90.0  | 90   | 0.0451          | 0.6347 | 0.7897 | 0.7895 | 0.7907 | 0.6807              | 0.7675           | 0.7213       |
+| 0.0056        | 100.0 | 100  | 0.0446          | 0.6353 | 0.7885 | 0.7889 | 0.7893 | 0.6807              | 0.7674           | 0.7213       |
 
 
 ### Framework versions

adapter_config.json

@@ -20,19 +20,19 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
+    "fc2",
+    "linear_1",
+    "k_proj",
+    "fc1",
+    "up_proj",
     "gate_proj",
+    "lm_head",
     "q_proj",
+    "linear_2",
     "out_proj",
     "down_proj",
-    "fc1",
-    "lm_head",
-    "fc2",
     "v_proj",
-    "up_proj",
-    "o_proj",
-    "k_proj",
-    "linear_2",
-    "linear_1"
+    "o_proj"
   ],
   "task_type": "CAUSAL_LM",
   "use_dora": false,

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training_args.bin

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