finetune-t5-base-on-opus100-Ar2En-with-lora

README.md

@@ -1,9 +1,6 @@
 ---
 base_model: UBC-NLP/AraT5v2-base-1024
 library_name: peft
-metrics:
-- bleu
-- rouge
 tags:
 - generated_from_trainer
 model-index:
@@ -14,16 +11,10 @@ model-index:
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/FinalProject_/T5/runs/vvxagyr8)
-[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/FinalProject_/T5/runs/vvxagyr8)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/FinalProject_/T5/runs/fy2nx2eb)
 # finetune-t5-base-on-opus100-Ar2En-with-lora
 
 This model is a fine-tuned version of [UBC-NLP/AraT5v2-base-1024](https://huggingface.co/UBC-NLP/AraT5v2-base-1024) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 3.7552
-- Bleu: 4.3018
-- Rouge: 0.2386
-- Gen Len: 10.572
 
 ## Model description
 
@@ -46,24 +37,13 @@ The following hyperparameters were used during training:
 - train_batch_size: 10
 - eval_batch_size: 10
 - seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 40
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 7
+- num_epochs: 37
 - mixed_precision_training: Native AMP
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Bleu   | Rouge  | Gen Len |
-|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|
-| 6.6745        | 1.0   | 700  | 4.6813          | 3.2487 | 0.2249 | 10.726  |
-| 6.1243        | 2.0   | 1400 | 4.0666          | 3.3995 | 0.2273 | 10.0245 |
-| 5.3863        | 3.0   | 2100 | 3.9208          | 3.8728 | 0.2335 | 10.3965 |
-| 5.1275        | 4.0   | 2800 | 3.8485          | 3.9535 | 0.2331 | 10.5655 |
-| 4.975         | 5.0   | 3500 | 3.7971          | 3.9941 | 0.2318 | 10.572  |
-| 4.8991        | 6.0   | 4200 | 3.7639          | 4.0786 | 0.2349 | 10.6005 |
-| 4.857         | 7.0   | 4900 | 3.7552          | 4.3018 | 0.2386 | 10.572  |
-
-
 ### Framework versions
 
 - PEFT 0.12.0

adapter_model.safetensors

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