Training complete

README.md

@@ -1,4 +1,5 @@
 ---
+library_name: transformers
 license: apache-2.0
 base_model: Helsinki-NLP/opus-mt-en-fr
 tags:
@@ -23,7 +24,7 @@ model-index:
     metrics:
     - name: Bleu
       type: bleu
-      value: 52.91210143343284
+      value: 52.95760336320957
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,8 +34,9 @@ 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: 0.8554
-- Bleu: 52.9121
+- Loss: 0.8556
+- Model Preparation Time: 0.0015
+- Bleu: 52.9576
 
 ## Model description
 
@@ -57,7 +59,7 @@ The following hyperparameters were used during training:
 - train_batch_size: 32
 - eval_batch_size: 64
 - seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - num_epochs: 3
 - mixed_precision_training: Native AMP
@@ -68,7 +70,7 @@ The following hyperparameters were used during training:
 
 ### Framework versions
 
-- Transformers 4.40.2
-- Pytorch 2.2.1+cu121
-- Datasets 2.19.1
-- Tokenizers 0.19.1
+- Transformers 4.46.2
+- Pytorch 2.1.0
+- Datasets 3.1.0
+- Tokenizers 0.20.3

generation_config.json

@@ -12,5 +12,5 @@
   "num_beams": 4,
   "pad_token_id": 59513,
   "renormalize_logits": true,
-  "transformers_version": "4.40.2"
+  "transformers_version": "4.46.2"
 }

runs/Feb10_19-41-04_AfterShock/events.out.tfevents.1739190256.AfterShock.721286.1

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+size 480