Training complete

README.md

@@ -2,6 +2,7 @@
 license: apache-2.0
 base_model: Helsinki-NLP/opus-mt-en-fr
 tags:
+- waquas/lab1_finetuning
 - generated_from_trainer
 datasets:
 - kde4
@@ -22,7 +23,7 @@ model-index:
     metrics:
     - name: Bleu
       type: bleu
-      value: 52.88398487672078
+      value: 49.75159108718876
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-fr](https://huggingface.co/Helsinki-NLP/opus-mt-en-fr) on the kde4 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8556
-- Bleu: 52.8840
+- Loss: 0.9966
+- Bleu: 49.7516
 
 ## Model description
 
@@ -53,12 +54,12 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 32
-- eval_batch_size: 64
+- train_batch_size: 64
+- eval_batch_size: 128
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 1
 - mixed_precision_training: Native AMP
 
 ### Training results
@@ -67,7 +68,7 @@ The following hyperparameters were used during training:
 
 ### Framework versions
 
-- Transformers 4.35.2
-- Pytorch 2.1.0+cu121
-- Datasets 2.17.0
-- Tokenizers 0.15.2
+- Transformers 4.37.0
+- Pytorch 2.1.2
+- Datasets 2.1.0
+- Tokenizers 0.15.1

generation_config.json

@@ -12,5 +12,5 @@
   "num_beams": 4,
   "pad_token_id": 59513,
   "renormalize_logits": true,
-  "transformers_version": "4.35.2"
+  "transformers_version": "4.37.0"
 }