Training in progress, step 500

README.md

@@ -1,6 +1,7 @@
 ---
 library_name: transformers
-base_model: siebert/sentiment-roberta-large-english
+license: mit
+base_model: FacebookAI/roberta-large
 tags:
 - generated_from_trainer
 metrics:
@@ -15,10 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # roberta-imdb
 
-This model is a fine-tuned version of [siebert/sentiment-roberta-large-english](https://huggingface.co/siebert/sentiment-roberta-large-english) on an unknown dataset.
+This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1137
-- Accuracy: 0.9612
+- Loss: 0.6932
+- Accuracy: 0.5
 
 ## Model description
 
@@ -37,25 +38,24 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 64
-- eval_batch_size: 64
+- learning_rate: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 30
+- lr_scheduler_type: linear
 - num_epochs: 1
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.0924        | 1.0   | 391  | 0.1137          | 0.9612   |
+| 0.5483        | 1.0   | 782  | 0.6932          | 0.5      |
 
 
 ### Framework versions
 
-- Transformers 4.46.3
+- Transformers 4.47.1
 - Pytorch 2.5.1+cu124
-- Datasets 3.1.0
-- Tokenizers 0.20.3
+- Datasets 3.2.0
+- Tokenizers 0.21.0

model.safetensors

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tokenizer.json

@@ -1,11 +1,6 @@
 {
   "version": "1.0",
-  "truncation": {
-    "direction": "Right",
-    "max_length": 512,
-    "strategy": "LongestFirst",
-    "stride": 0
-  },
+  "truncation": null,
   "padding": null,
   "added_tokens": [
     {

training_args.bin

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