num_labels=n_classes ) self.model.config.id2label = {k: v for k, v in enumerate(DOCUMENT_CLASSES)} self.model.config.label2id = {v: k for k, v in enumerate(DOCUMENT_CLASSES)}
line 315, in main trainer.train( File "/mnt/nvme1/code/huggingface/transformers-master/src/transformers/trainer.py", line 821, in train self.optimizer.step() File "/home/stas/anaconda3/envs/main-38/lib/python3.8/site-packages/torch/optim/lr_scheduler.py", line 65, in wrapper...
'train')),eval=self._SummaryWriter(log_dir=os.path.join(log_dir,'eval')))defon_train_begin(self, args, state, control, **kwargs):ifnotstate.is_world_process_zero:returnlog_dir =Noneifstate.is_hyper_param_search:
There is no problem in a fresh install until i install dreambooth and then things fall apart. Spent hours yesterday and today trying to fix it. I just dropped the entire log as far as it reaches back from my current console. It runs but it is insane how utterly broken it is. And on...
oc logs pod/mnist-training-master-0 -n huggingface Test Epoch (1): Avg. Loss = 0.391768, Acc. = 2999/3334 (% 89.95) Test Epoch (2): Avg. Loss = 0.215838, Acc. = 3145/3334 (% 94.33) Test Epoch (3): Avg. Loss = 0.153547, Acc. = 3172/3334 (% 95.14) ...
Axolotl also uses the 🤗Trainer API, and has a number of features for custom evaluation and logging. You can evaluate on MMLU, or a local benchmark dataset and log loss/ accuracy during training. Axolotl further supports both FSDP and DeepSpeed, mainly because they just let the Trainer hand...
(or the softmax for multi-class) for classification and the identity function for regression. In both cases, we addℓ2regularization over the parameterswin Eq. (3) and minimize the loss (cross-entropy for classification, mean-squared error for regression) using Limited memory BFGS (...
这里的c_truncated_reward.shape = torch.Size([109]),同理r_truncated_reward.shape也为torch.Size([109]),也就是找出c_truncated_reward和r_truncated_reward经过一个线性层之后不同的地方,然后针对这两者球logsigmoid(c_truncated_reward - r_truncated_reward).mean,返回loss即可。
Hopefully you’re getting an intuition about what’s happening under the hood to train a CausalLM model using HuggingFace. You might have some questions like “why do we need labels as a separate array when we could just use the kth index of input_ids directly at each step? Is there...
How to continue training with HuggingFace Trainer? Load 3 more related questionsShow fewer related questions Know someone who can answer? Share a link to thisquestionviaemail,Twitter, orFacebook. Your Answer Sign up using Google Sign up using Email and Password ...