Update README.md

README.md

@@ -3,33 +3,30 @@ license: apache-2.0
 base_model: distilroberta-base
 tags:
 - generated_from_trainer
-model-index:
-- name: distilroberta-base-fineweb-edu-llama3-annotations-2048-vN
-  results: []
+inference: false
+datasets:
+- HuggingFaceFW/fineweb-edu-llama3-annotations
+language:
+- en
+metrics:
+- mse
 ---
 
-<!-- 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. -->
 
 [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/pszemraj/eduscore-regression/runs/8e2uvp5t)
-# distilroberta-base-fineweb-edu-llama3-annotations-2048-vN
+# distilroberta-base-edu-classifier
+
 
 This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the HuggingFaceFW/fineweb-edu-llama3-annotations dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.2194
 - Mse: 0.2194
 
-## Model description
-
-More information needed
 
-## Intended uses & limitations
+## Usage 
 
-More information needed
 
-## Training and evaluation data
-
-More information needed
+Same as the others, will add later
 
 ## Training procedure
 
@@ -46,50 +43,3 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.05
 - num_epochs: 1.0
-
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss | Mse    |
-|:-------------:|:------:|:----:|:---------------:|:------:|
-| 0.5276        | 0.0288 | 100  | 0.5012          | 0.5012 |
-| 0.3307        | 0.0576 | 200  | 0.3467          | 0.3467 |
-| 0.2994        | 0.0865 | 300  | 0.2948          | 0.2948 |
-| 0.2813        | 0.1153 | 400  | 0.2799          | 0.2799 |
-| 0.2707        | 0.1441 | 500  | 0.3017          | 0.3017 |
-| 0.2506        | 0.1729 | 600  | 0.2699          | 0.2699 |
-| 0.2584        | 0.2018 | 700  | 0.2633          | 0.2633 |
-| 0.2603        | 0.2306 | 800  | 0.2434          | 0.2434 |
-| 0.2973        | 0.2594 | 900  | 0.2394          | 0.2394 |
-| 0.2541        | 0.2882 | 1000 | 0.2356          | 0.2356 |
-| 0.2837        | 0.3171 | 1100 | 0.2437          | 0.2437 |
-| 0.242         | 0.3459 | 1200 | 0.2379          | 0.2379 |
-| 0.2379        | 0.3747 | 1300 | 0.2270          | 0.2270 |
-| 0.23          | 0.4035 | 1400 | 0.2357          | 0.2357 |
-| 0.2345        | 0.4324 | 1500 | 0.2417          | 0.2417 |
-| 0.2574        | 0.4612 | 1600 | 0.2556          | 0.2556 |
-| 0.264         | 0.4900 | 1700 | 0.2452          | 0.2452 |
-| 0.2596        | 0.5188 | 1800 | 0.2215          | 0.2215 |
-| 0.244         | 0.5477 | 1900 | 0.2269          | 0.2269 |
-| 0.2225        | 0.5765 | 2000 | 0.2342          | 0.2342 |
-| 0.2475        | 0.6053 | 2100 | 0.2403          | 0.2403 |
-| 0.253         | 0.6341 | 2200 | 0.2326          | 0.2326 |
-| 0.2435        | 0.6630 | 2300 | 0.2161          | 0.2161 |
-| 0.2865        | 0.6918 | 2400 | 0.2265          | 0.2265 |
-| 0.2351        | 0.7206 | 2500 | 0.2343          | 0.2343 |
-| 0.2582        | 0.7494 | 2600 | 0.2342          | 0.2342 |
-| 0.2167        | 0.7783 | 2700 | 0.2337          | 0.2337 |
-| 0.2495        | 0.8071 | 2800 | 0.2273          | 0.2273 |
-| 0.2364        | 0.8359 | 2900 | 0.2298          | 0.2298 |
-| 0.2236        | 0.8647 | 3000 | 0.2170          | 0.2170 |
-| 0.231         | 0.8936 | 3100 | 0.2234          | 0.2234 |
-| 0.2474        | 0.9224 | 3200 | 0.2227          | 0.2227 |
-| 0.2333        | 0.9512 | 3300 | 0.2241          | 0.2241 |
-| 0.2265        | 0.9800 | 3400 | 0.2197          | 0.2197 |
-
-
-### Framework versions
-
-- Transformers 4.42.3
-- Pytorch 2.3.1+cu121
-- Datasets 2.20.0
-- Tokenizers 0.19.1