Comments (4)
Two things to take note of here.
- ensure you're not using cross attention between documents.
- ensure that you're not using subword or word level but character level.
Thanks
from long-range-arena.
Thanks for replying.
-
I am also use two tower style model
token_out_0 = self.model(input_ids_0, mask_0)
token_out_1 = self.model(input_ids_1, mask_1)
seq_scores = self.seq_classifer(token_out_0, token_out_1)
Within self.seq_classifer, the following is computed:
X_0 = pooling(token_out_0, self.pooling_mode)
X_1 = pooling(token_out_1, self.pooling_mode)
seq_scores = self.mlpblock(torch.cat([X_0, X_1, X_0 * X_1, X_0 - X_1], dim = -1))
-
I use the input_pipeline.get_matching_datasets to generate data and tokenizer is set to "char"
train_ds, eval_ds, test_ds, encoder = input_pipeline.get_matching_datasets(
n_devices = 1, task_name = None, data_dir = "../../lra_release/lra_release/tsv_data/",
batch_size = 1, fixed_vocab = None, max_length = 4000, tokenizer = "char",
vocab_file_path = None)
from long-range-arena.
@mlpen How many training steps and warmup did you use? Config says to use 5K training steps and 8K warmup steps, but that feels weird.
from long-range-arena.
That's because we used some default FLAX code and only did cursory sweep of hparams (hparam sweeps not within scope of the paper). Some other folks have found that training longer leads to better performance, hence I recommend works like https://arxiv.org/abs/2106.01540 and follow their setup. Thanks :)
from long-range-arena.
Related Issues (20)
- bug in Pathfinder-128 dataset HOT 9
- Error in matching task
- Perceiver on LRA
- Pathfinder not learning three times in a row. HOT 1
- Error when run document retrival HOT 3
- Request about cuda version when using GPUs HOT 4
- Quadratic Longformer suspicion HOT 1
- Dataset for the matching task HOT 1
- Are encoder and decoder both implemented with sparse attention for bigbird? How long is the verified output length for the decoder?
- Current code doesn't work with latest flax version and run on CPU only HOT 15
- The best checkpoint of Transformer
- AAN dataset unavailable HOT 1
- AAN dataset crashing when loading .tsv file HOT 4
- ModuleNotFoundError: No module named 'flax.deprecated' HOT 3
- How to use the pathfinder.py code to generate the dataset? HOT 1
- Pretrained models
- Is there a pytorch equivalent of this implementation? HOT 2
- Question regarding model checkpoint
- Question regarding Pathfinder and Listops performance HOT 2
- Is it really byte-level?
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from long-range-arena.