Training complete!

README.md

@@ -1,14 +1,12 @@
 ---
-library_name: transformers
-license: apache-2.0
 base_model: google/t5-efficient-tiny-nh8
+library_name: peft
+license: apache-2.0
 tags:
 - generated_from_trainer
 model-index:
 - name: t5-efficient-tiny-nh8-summarizer
   results: []
-datasets: 
-- shorecode/summary-collection-60k-rows
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,30 +14,26 @@ should probably proofread and complete it, then remove this comment. -->
 
 # t5-efficient-tiny-nh8-summarizer
 
-This model is a fine-tuned version of [shorecode/t5-efficient-tiny-nh8-summarizer](https://huggingface.co/shorecode/t5-efficient-tiny-nh8-summarizer) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.6597
+This model is a fine-tuned version of [google/t5-efficient-tiny-nh8](https://huggingface.co/google/t5-efficient-tiny-nh8) on an unknown dataset.
 
 ## Model description
 
-A general purpose text summarizer
+More information needed
 
 ## Intended uses & limitations
 
-General purpose text summarizer
+More information needed
 
 ## Training and evaluation data
 
-Trained and evaluated on shorecode/summary-collection-60k-rows
+More information needed
 
 ## Training procedure
 
-Trained using the Gradio SDK on Hugging Face Spaces using shared Zero GPU(s)
-
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.00015000000000000001
+- learning_rate: 0.0002
 - train_batch_size: 63
 - eval_batch_size: 63
 - seed: 42
@@ -50,24 +44,12 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| 1.0837        | 0.2663 | 200  | 0.9227          |
-| 0.9027        | 0.5326 | 400  | 0.8449          |
-| 0.842         | 0.7989 | 600  | 0.7949          |
-| 0.7971        | 1.0652 | 800  | 0.7585          |
-| 0.768         | 1.3316 | 1000 | 0.7288          |
-| 0.7359        | 1.5979 | 1200 | 0.7069          |
-| 0.7145        | 1.8642 | 1400 | 0.6898          |
-| 0.7047        | 2.1305 | 1600 | 0.6773          |
-| 0.6926        | 2.3968 | 1800 | 0.6678          |
-| 0.6855        | 2.6631 | 2000 | 0.6620          |
-| 0.68          | 2.9294 | 2200 | 0.6597          |
 
 
 ### Framework versions
 
+- PEFT 0.14.0
 - Transformers 4.47.0
 - Pytorch 2.4.0+cu121
 - Datasets 3.0.0
-- Tokenizers 0.21.0
+- Tokenizers 0.21.0

adapter_config.json

@@ -4,7 +4,7 @@
     "base_model_class": "T5ForConditionalGeneration",
     "parent_library": "transformers.models.t5.modeling_t5"
   },
-  "base_model_name_or_path": "google/t5-efficient-tiny",
+  "base_model_name_or_path": "google/t5-efficient-tiny-nh8",
   "bias": "none",
   "eva_config": null,
   "exclude_modules": null,
@@ -15,19 +15,19 @@
   "layers_pattern": null,
   "layers_to_transform": null,
   "loftq_config": {},
-  "lora_alpha": 32,
+  "lora_alpha": 8,
   "lora_bias": false,
   "lora_dropout": 0.1,
   "megatron_config": null,
   "megatron_core": "megatron.core",
   "modules_to_save": null,
   "peft_type": "LORA",
-  "r": 16,
+  "r": 4,
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "q",
-    "v"
+    "v",
+    "q"
   ],
   "task_type": null,
   "use_dora": false,

adapter_model.safetensors

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training_args.bin

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