ubaada/long-t5-tglobal-base-booksum

README.md

@@ -17,10 +17,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.9730
-- Rouge1: 0.1342
-- Rouge2: 0.0151
-- Rougel: 0.0912
+- Loss: 1.9565
+- Rouge1: 0.1423
+- Rouge2: 0.0178
+- Rougel: 0.0928
 
 ## Model description
 
@@ -50,13 +50,15 @@ The following hyperparameters were used during training:
 - total_eval_batch_size: 2
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 1
+- num_epochs: 3
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
 |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|
 | 1.5731        | 0.9996 | 600  | 1.9730          | 0.1342 | 0.0151 | 0.0912 |
+| 1.3694        | 1.9996 | 1200 | 1.9623          | 0.1371 | 0.0175 | 0.0909 |
+| 1.9561        | 2.9992 | 1800 | 1.9565          | 0.1423 | 0.0178 | 0.0928 |
 
 
 ### Framework versions

model.safetensors

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 size 990386200

tokenizer.json

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-    "strategy": "LongestFirst",
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-    "pad_to_multiple_of": null,
-    "pad_id": 0,
-    "pad_type_id": 0,
-    "pad_token": "<pad>"
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+  "truncation": null,
+  "padding": null,
   "added_tokens": [
     {
       "id": 0,

training_args.bin

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 size 6776