finetuned-bart-large-samsum

README.md

@@ -5,12 +5,10 @@ tags:
 - generated_from_trainer
 metrics:
 - rouge
+- bleu
 model-index:
 - name: bart_samsum
   results: []
-datasets:
-- samsum
-pipeline_tag: summarization
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,14 +16,16 @@ should probably proofread and complete it, then remove this comment. -->
 
 # bart_samsum
 
-This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the samsum dataset.
+This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.4684
-- Rouge1: 53.1615
-- Rouge2: 28.3187
-- Rougel: 43.9981
-- Rougelsum: 49.0956
-- Gen Len: 29.8974
+- Loss: 1.4947
+- Rouge1: 53.3294
+- Rouge2: 28.6009
+- Rougel: 44.2008
+- Rougelsum: 49.2031
+- Bleu: 0.0
+- Meteor: 0.4887
+- Gen Len: 30.1209
 
 ## Model description
 
@@ -52,22 +52,23 @@ The following hyperparameters were used during training:
 - total_train_batch_size: 8
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 4
+- num_epochs: 5
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
-| 1.3821        | 1.0   | 1841 | 1.5259          | 52.3728 | 27.326  | 42.9657 | 48.1683   | 30.6093 |
-| 1.0795        | 2.0   | 3683 | 1.4684          | 53.1615 | 28.3187 | 43.9981 | 49.0956   | 29.8974 |
-| 0.831         | 3.0   | 5524 | 1.5446          | 53.2242 | 27.9402 | 43.7724 | 48.6376   | 29.9438 |
-| 0.693         | 4.0   | 7364 | 1.6323          | 52.7069 | 27.8821 | 43.516  | 48.382    | 30.3822 |
+| Training Loss | Epoch  | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bleu | Meteor | Gen Len |
+|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:----:|:------:|:-------:|
+| 1.3838        | 0.9997 | 1841 | 1.5631          | 52.3252 | 27.2646 | 42.5893 | 48.2397   | 0.0  | 0.4825 | 32.0415 |
+| 1.0835        | 2.0    | 3683 | 1.4947          | 53.3294 | 28.6009 | 44.2008 | 49.2031   | 0.0  | 0.4887 | 30.1209 |
+| 0.8345        | 2.9997 | 5524 | 1.5956          | 52.1812 | 27.1239 | 42.9864 | 47.6384   | 0.0  | 0.4774 | 30.5446 |
+| 0.672         | 4.0    | 7366 | 1.6695          | 52.8148 | 27.4815 | 43.3732 | 48.4633   | 0.0  | 0.4836 | 31.0342 |
+| 0.538         | 4.9986 | 9205 | 1.8055          | 52.0988 | 26.762  | 42.5505 | 47.3721   | 0.0  | 0.4738 | 29.8901 |
 
 
 ### Framework versions
 
-- Transformers 4.38.2
+- Transformers 4.40.0
 - Pytorch 2.2.1+cu121
 - Datasets 2.19.0
-- Tokenizers 0.15.2
+- Tokenizers 0.19.1

config.json

@@ -61,7 +61,7 @@
   "student_encoder_layers": null,
   "task_specific_params": {},
   "torch_dtype": "float32",
-  "transformers_version": "4.38.2",
+  "transformers_version": "4.40.0",
   "use_cache": true,
   "vocab_size": 50264
 }

generation_config.json

@@ -9,5 +9,5 @@
   "no_repeat_ngram_size": 3,
   "num_beams": 6,
   "pad_token_id": 1,
-  "transformers_version": "4.38.2"
+  "transformers_version": "4.40.0"
 }

model.safetensors

@@ -1,3 +1,3 @@
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 size 1625422896

training_args.bin

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