Training complete

README.md

@@ -1,41 +1,26 @@
 ---
 license: mit
-base_model: kazandaev/m2m100_418M
+base_model: facebook/m2m100_418M
 tags:
 - translation
 - generated_from_trainer
-datasets:
-- wmt16
 metrics:
 - bleu
 model-index:
-- name: m2m100_418M
-  results:
-  - task:
-      name: Sequence-to-sequence Language Modeling
-      type: text2text-generation
-    dataset:
-      name: wmt16
-      type: wmt16
-      config: ru-en
-      split: validation
-      args: ru-en
-    metrics:
-    - name: Bleu
-      type: bleu
-      value: 32.0585
+- name: m2m100_418M-finetuned-en-ru
+  results: []
 ---
 
 <!-- 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. -->
 
-# m2m100_418M
+# m2m100_418M-finetuned-en-ru
 
-This model is a fine-tuned version of [kazandaev/m2m100_418M](https://huggingface.co/kazandaev/m2m100_418M) on the wmt16 dataset.
+This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8954
-- Bleu: 32.0585
-- Gen Len: 36.1643
+- Loss: 0.6798
+- Bleu: 51.7753
+- Gen Len: 61.5271
 
 ## Model description
 
@@ -56,20 +41,28 @@ More information needed
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
 - train_batch_size: 4
-- eval_batch_size: 2
+- eval_batch_size: 3
 - seed: 42
-- gradient_accumulation_steps: 10
-- total_train_batch_size: 40
+- gradient_accumulation_steps: 50
+- total_train_batch_size: 200
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 2
+- num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
 |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
-| 0.8087        | 1.0   | 47790 | 0.9542          | 30.786  | 36.1469 |
-| 0.7266        | 2.0   | 95580 | 0.8954          | 32.0585 | 36.1643 |
+| 0.8981        | 1.0   | 9218  | 0.8277          | 48.5181 | 61.4701 |
+| 0.8167        | 2.0   | 18437 | 0.7696          | 49.6956 | 61.4641 |
+| 0.7718        | 3.0   | 27656 | 0.7396          | 50.4045 | 61.5042 |
+| 0.7373        | 4.0   | 36875 | 0.7203          | 50.8134 | 61.5313 |
+| 0.713         | 5.0   | 46094 | 0.7069          | 51.136  | 61.5931 |
+| 0.6937        | 6.0   | 55312 | 0.6967          | 51.4274 | 61.5911 |
+| 0.6787        | 7.0   | 64531 | 0.6889          | 51.5404 | 61.5012 |
+| 0.6659        | 8.0   | 73750 | 0.6844          | 51.7187 | 61.5229 |
+| 0.6584        | 9.0   | 82969 | 0.6809          | 51.8218 | 61.5392 |
+| 0.649         | 10.0  | 92180 | 0.6798          | 51.7753 | 61.5271 |
 
 
 ### Framework versions