Update README.md

README.md

@@ -14,7 +14,6 @@ datasets:
 - openbookqa
 - mandyyyyii/scibench
 - derek-thomas/ScienceQA
-- wenhu/TheoremQA
 - TIGER-Lab/ScienceEval
 - jondurbin/airoboros-3.2
 - LDJnr/Capybara
@@ -155,50 +154,3 @@ resume_from_checkpoint: Einstein-v4-model/checkpoint-521
 This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.4902
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 5e-06
-- train_batch_size: 1
-- eval_batch_size: 1
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 8
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 32
-- total_eval_batch_size: 8
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 10
-- num_epochs: 1.5
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss |
-|:-------------:|:-----:|:----:|:---------------:|
-| 1.1358        | 0.0   | 1    | 1.2075          |
-| 0.5083        | 0.5   | 521  | 0.5161          |
-| 0.4759        | 1.0   | 1042 | 0.4902          |
-
-
-### Framework versions
-
-- Transformers 4.38.0.dev0
-- Pytorch 2.1.2+cu118
-- Datasets 2.16.1
-- Tokenizers 0.15.0